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Wang Z, Guo J, van 't Klooster M, Hoogteijling S, Jacobs J, Zijlmans M. Prognostic Value of Complete Resection of the High-Frequency Oscillation Area in Intracranial EEG: A Systematic Review and Meta-Analysis. Neurology 2024; 102:e209216. [PMID: 38560817 DOI: 10.1212/wnl.0000000000209216] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/19/2023] [Accepted: 01/12/2024] [Indexed: 04/04/2024] Open
Abstract
BACKGROUND AND OBJECTIVES High-frequency oscillations (HFOs; ripples 80-250 Hz; fast ripples [FRs] 250-500 Hz) recorded with intracranial electrodes generated excitement and debate about their potential to localize epileptogenic foci. We performed a systematic review and meta-analysis on the prognostic value of complete resection of the HFOs-area (crHFOs-area) for epilepsy surgical outcome in intracranial EEG (iEEG) accessing multiple subgroups. METHODS We searched PubMed, Embase, and Web of Science for original research from inception to October 27, 2022. We defined favorable surgical outcome (FSO) as Engel class I, International League Against Epilepsy class 1, or seizure-free status. The prognostic value of crHFOs-area for FSO was assessed by (1) the pooled FSO proportion after crHFOs-area; (2) FSO for crHFOs-area vs without crHFOs-area; and (3) the predictive performance. We defined high combined prognostic value as FSO proportion >80% + FSO crHFOs-area >without crHFOs-area + area under the curve (AUC) >0.75 and examined this for the clinical subgroups (study design, age, diagnostic type, HFOs-identification method, HFOs-rate thresholding, and iEEG state). Temporal lobe epilepsy (TLE) was compared with extra-TLE through dichotomous variable analysis. Individual patient analysis was performed for sex, affected hemisphere, MRI findings, surgery location, and pathology. RESULTS Of 1,387 studies screened, 31 studies (703 patients) met our eligibility criteria. Twenty-seven studies (602 patients) analyzed FRs and 20 studies (424 patients) ripples. Pooled FSO proportion after crHFOs-area was 81% (95% CI 76%-86%) for FRs and 82% (73%-89%) for ripples. Patients with crHFOs-area achieved more often FSO than those without crHFOs-area (FRs odds ratio [OR] 6.38, 4.03-10.09, p < 0.001; ripples 4.04, 2.32-7.04, p < 0.001). The pooled AUCs were 0.81 (0.77-0.84) for FRs and 0.76 (0.72-0.79) for ripples. Combined prognostic value was high in 10 subgroups: retrospective, children, long-term iEEG, threshold (FRs and ripples) and automated detection and interictal (FRs). FSO after complete resection of FRs-area (crFRs-area) was achieved less often in people with TLE than extra-TLE (OR 0.37, 0.15-0.89, p = 0.006). Individual patient analyses showed that crFRs-area was seen more in patients with FSO with than without MRI lesions (p = 0.02 after multiple correction). DISCUSSION Complete resection of the brain area with HFOs is associated with good postsurgical outcome. Its prognostic value holds, especially for FRs, for various subgroups. The use of HFOs for extra-TLE patients requires further evidence.
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Affiliation(s)
- Ziyi Wang
- From the Department of Neurology and Neurosurgery (Z.W., J.G., M.v.t.K., S.H., M.Z.), University Medical Center Utrecht Brain Center, University Medical Center Utrecht, Part of ERN EpiCARE, the Netherlands; Department of Pediatrics (J.J.), University of Calgary, Alberta Children's Hospital, Calgary, Canada; and Stichting Epilepsie Instellingen Nederland (SEIN) (M.Z.), Heemstede, the Netherlands
| | - Jiaojiao Guo
- From the Department of Neurology and Neurosurgery (Z.W., J.G., M.v.t.K., S.H., M.Z.), University Medical Center Utrecht Brain Center, University Medical Center Utrecht, Part of ERN EpiCARE, the Netherlands; Department of Pediatrics (J.J.), University of Calgary, Alberta Children's Hospital, Calgary, Canada; and Stichting Epilepsie Instellingen Nederland (SEIN) (M.Z.), Heemstede, the Netherlands
| | - Maryse van 't Klooster
- From the Department of Neurology and Neurosurgery (Z.W., J.G., M.v.t.K., S.H., M.Z.), University Medical Center Utrecht Brain Center, University Medical Center Utrecht, Part of ERN EpiCARE, the Netherlands; Department of Pediatrics (J.J.), University of Calgary, Alberta Children's Hospital, Calgary, Canada; and Stichting Epilepsie Instellingen Nederland (SEIN) (M.Z.), Heemstede, the Netherlands
| | - Sem Hoogteijling
- From the Department of Neurology and Neurosurgery (Z.W., J.G., M.v.t.K., S.H., M.Z.), University Medical Center Utrecht Brain Center, University Medical Center Utrecht, Part of ERN EpiCARE, the Netherlands; Department of Pediatrics (J.J.), University of Calgary, Alberta Children's Hospital, Calgary, Canada; and Stichting Epilepsie Instellingen Nederland (SEIN) (M.Z.), Heemstede, the Netherlands
| | - Julia Jacobs
- From the Department of Neurology and Neurosurgery (Z.W., J.G., M.v.t.K., S.H., M.Z.), University Medical Center Utrecht Brain Center, University Medical Center Utrecht, Part of ERN EpiCARE, the Netherlands; Department of Pediatrics (J.J.), University of Calgary, Alberta Children's Hospital, Calgary, Canada; and Stichting Epilepsie Instellingen Nederland (SEIN) (M.Z.), Heemstede, the Netherlands
| | - Maeike Zijlmans
- From the Department of Neurology and Neurosurgery (Z.W., J.G., M.v.t.K., S.H., M.Z.), University Medical Center Utrecht Brain Center, University Medical Center Utrecht, Part of ERN EpiCARE, the Netherlands; Department of Pediatrics (J.J.), University of Calgary, Alberta Children's Hospital, Calgary, Canada; and Stichting Epilepsie Instellingen Nederland (SEIN) (M.Z.), Heemstede, the Netherlands
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Remakanthakurup Sindhu K, Phan C, Anis S, Riba A, Garner C, Magers AL, Tran N, Maser AL, Simon KC, Mednick SC, Shrey DW, Lopour BA. Physiological ripples during sleep in scalp electroencephalogram of healthy infants. Sleep 2023; 46:zsad247. [PMID: 37816242 PMCID: PMC10710989 DOI: 10.1093/sleep/zsad247] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/12/2023] Open
Affiliation(s)
| | - Christopher Phan
- Department of Biomedical Engineering, University of California, Irvine, Irvine, CA, USA
| | - Sara Anis
- Department of Biomedical Engineering, University of California, Irvine, Irvine, CA, USA
| | - Aliza Riba
- Division of Neurology, Children’s Hospital of Orange County, Orange, CA, USA
| | - Cristal Garner
- Division of Neurology, Children’s Hospital of Orange County, Orange, CA, USA
| | - Amber L Magers
- Division of Neurology, Children’s Hospital of Orange County, Orange, CA, USA
| | - Nhi Tran
- Division of Neurology, Children’s Hospital of Orange County, Orange, CA, USA
| | - Amy L Maser
- Division of Neurology, Children’s Hospital of Orange County, Orange, CA, USA
| | - Katharine C Simon
- Department of Cognitive Sciences, University of California, Irvine, Irvine, CA, USA
| | - Sara C Mednick
- Department of Cognitive Sciences, University of California, Irvine, Irvine, CA, USA
| | - Daniel W Shrey
- Division of Neurology, Children’s Hospital of Orange County, Orange, CA, USA
- Department of Pediatrics, University of California, Irvine, Irvine, CA, USA
| | - Beth A Lopour
- Department of Biomedical Engineering, University of California, Irvine, Irvine, CA, USA
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3
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Yeh CH, Zhang C, Shi W, Lo MT, Tinkhauser G, Oswal A. Cross-Frequency Coupling and Intelligent Neuromodulation. Cyborg Bionic Syst 2023; 4:0034. [PMID: 37266026 PMCID: PMC10231647 DOI: 10.34133/cbsystems.0034] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/03/2023] [Accepted: 05/02/2023] [Indexed: 06/03/2023] Open
Abstract
Cross-frequency coupling (CFC) reflects (nonlinear) interactions between signals of different frequencies. Evidence from both patient and healthy participant studies suggests that CFC plays an essential role in neuronal computation, interregional interaction, and disease pathophysiology. The present review discusses methodological advances and challenges in the computation of CFC with particular emphasis on potential solutions to spurious coupling, inferring intrinsic rhythms in a targeted frequency band, and causal interferences. We specifically focus on the literature exploring CFC in the context of cognition/memory tasks, sleep, and neurological disorders, such as Alzheimer's disease, epilepsy, and Parkinson's disease. Furthermore, we highlight the implication of CFC in the context and for the optimization of invasive and noninvasive neuromodulation and rehabilitation. Mainly, CFC could support advancing the understanding of the neurophysiology of cognition and motor control, serve as a biomarker for disease symptoms, and leverage the optimization of therapeutic interventions, e.g., closed-loop brain stimulation. Despite the evident advantages of CFC as an investigative and translational tool in neuroscience, further methodological improvements are required to facilitate practical and correct use in cyborg and bionic systems in the field.
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Affiliation(s)
- Chien-Hung Yeh
- School of Information and Electronics,
Beijing Institute of Technology, Beijing, China
| | - Chuting Zhang
- School of Information and Electronics,
Beijing Institute of Technology, Beijing, China
| | - Wenbin Shi
- School of Information and Electronics,
Beijing Institute of Technology, Beijing, China
| | - Men-Tzung Lo
- Department of Biomedical Sciences and Engineering,
National Central University, Taoyuan, Taiwan
| | - Gerd Tinkhauser
- Department of Neurology,
Bern University Hospital and University of Bern, Bern, Switzerland
| | - Ashwini Oswal
- MRC Brain Network Dynamics Unit,
University of Oxford, Oxford, UK
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Drew VJ, Wang C, Kim T. Progressive sleep disturbance in various transgenic mouse models of Alzheimer's disease. Front Aging Neurosci 2023; 15:1119810. [PMID: 37273656 PMCID: PMC10235623 DOI: 10.3389/fnagi.2023.1119810] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/09/2022] [Accepted: 04/24/2023] [Indexed: 06/06/2023] Open
Abstract
Alzheimer's disease (AD) is the leading cause of dementia. The relationship between AD and sleep dysfunction has received increased attention over the past decade. The use of genetically engineered mouse models with enhanced production of amyloid beta (Aβ) or hyperphosphorylated tau has played a critical role in the understanding of the pathophysiology of AD. However, their revelations regarding the progression of sleep impairment in AD have been highly dependent on the mouse model used and the specific techniques employed to examine sleep. Here, we discuss the sleep disturbances and general pathology of 15 mouse models of AD. Sleep disturbances covered in this review include changes to NREM and REM sleep duration, bout lengths, bout counts and power spectra. Our aim is to describe in detail the severity and chronology of sleep disturbances within individual mouse models of AD, as well as reveal broader trends of sleep deterioration that are shared among most models. This review also explores a variety of potential mechanisms relating Aβ accumulation and tau neurofibrillary tangles to the progressive deterioration of sleep observed in AD. Lastly, this review offers perspective on how study design might impact our current understanding of sleep disturbances in AD and provides strategies for future research.
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Affiliation(s)
- Victor J. Drew
- Department of Biomedical Science and Engineering, Gwangju Institute of Science and Technology, Gwangju, Republic of Korea
| | - Chanung Wang
- Department of Neurology, Washington University School of Medicine, St. Louis, MO, United States
| | - Tae Kim
- Department of Biomedical Science and Engineering, Gwangju Institute of Science and Technology, Gwangju, Republic of Korea
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Thomas J, Kahane P, Abdallah C, Avigdor T, Zweiphenning WJEM, Chabardes S, Jaber K, Latreille V, Minotti L, Hall J, Dubeau F, Gotman J, Frauscher B. A Subpopulation of Spikes Predicts Successful Epilepsy Surgery Outcome. Ann Neurol 2023; 93:522-535. [PMID: 36373178 DOI: 10.1002/ana.26548] [Citation(s) in RCA: 18] [Impact Index Per Article: 18.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/20/2022] [Revised: 11/09/2022] [Accepted: 11/11/2022] [Indexed: 11/15/2022]
Abstract
OBJECTIVE Epileptic spikes are the traditional interictal electroencephalographic (EEG) biomarker for epilepsy. Given their low specificity for identifying the epileptogenic zone (EZ), they are given only moderate attention in presurgical evaluation. This study aims to demonstrate that it is possible to identify specific spike features in intracranial EEG that optimally define the EZ and predict surgical outcome. METHODS We analyzed spike features on stereo-EEG segments from 83 operated patients from 2 epilepsy centers (37 Engel IA) in wakefulness, non-rapid eye movement sleep, and rapid eye movement sleep. After automated spike detection, we investigated 135 spike features based on rate, morphology, propagation, and energy to determine the best feature or feature combination to discriminate the EZ in seizure-free and non-seizure-free patients by applying 4-fold cross-validation. RESULTS The rate of spikes with preceding gamma activity in wakefulness performed better for surgical outcome classification (4-fold area under receiver operating characteristics curve [AUC] = 0.755 ± 0.07) than the seizure onset zone, the current gold standard (AUC = 0.563 ± 0.05, p = 0.015) and the ripple rate, an emerging seizure-independent biomarker (AUC = 0.537 ± 0.07, p = 0.006). Channels with a spike-gamma rate exceeding 1.9/min had an 80% probability of being in the EZ. Combining features did not improve the results. INTERPRETATION Resection of brain regions with high spike-gamma rates in wakefulness is associated with a high probability of achieving seizure freedom. This rate could be applied to determine the minimal number of spiking channels requiring resection. In addition to quantitative analysis, this feature is easily accessible to visual analysis, which could aid clinicians during presurgical evaluation. ANN NEUROL 2023;93:522-535.
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Affiliation(s)
- John Thomas
- Montreal Neurological Institute and Hospital, McGill University, Montreal, Quebec, Canada
| | - Philippe Kahane
- Grenoble Alpes University Hospital Center, Grenoble Alpes University, Inserm, U1216, Grenoble Institute Neurosciences, Grenoble, France
| | - Chifaou Abdallah
- Montreal Neurological Institute and Hospital, McGill University, Montreal, Quebec, Canada
| | - Tamir Avigdor
- Montreal Neurological Institute and Hospital, McGill University, Montreal, Quebec, Canada
| | - Willemiek J E M Zweiphenning
- Montreal Neurological Institute and Hospital, McGill University, Montreal, Quebec, Canada.,University Medical Center Utrecht, Utrecht University, Utrecht, the Netherlands
| | - Stephan Chabardes
- Grenoble Alpes University Hospital Center, Grenoble Alpes University, Inserm, U1216, Grenoble Institute Neurosciences, Grenoble, France
| | - Kassem Jaber
- Montreal Neurological Institute and Hospital, McGill University, Montreal, Quebec, Canada
| | - Véronique Latreille
- Montreal Neurological Institute and Hospital, McGill University, Montreal, Quebec, Canada
| | - Lorella Minotti
- Grenoble Alpes University Hospital Center, Grenoble Alpes University, Inserm, U1216, Grenoble Institute Neurosciences, Grenoble, France
| | - Jeff Hall
- Montreal Neurological Institute and Hospital, McGill University, Montreal, Quebec, Canada
| | - François Dubeau
- Montreal Neurological Institute and Hospital, McGill University, Montreal, Quebec, Canada
| | - Jean Gotman
- Montreal Neurological Institute and Hospital, McGill University, Montreal, Quebec, Canada
| | - Birgit Frauscher
- Montreal Neurological Institute and Hospital, McGill University, Montreal, Quebec, Canada
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Karpychev V, Balatskaya A, Utyashev N, Pedyash N, Zuev A, Dragoy O, Fedele T. Epileptogenic high-frequency oscillations present larger amplitude both in mesial temporal and neocortical regions. Front Hum Neurosci 2022; 16:984306. [PMID: 36248681 PMCID: PMC9557004 DOI: 10.3389/fnhum.2022.984306] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/01/2022] [Accepted: 09/12/2022] [Indexed: 11/17/2022] Open
Abstract
High-frequency oscillations (HFO) are a promising biomarker for the identification of epileptogenic tissue. While HFO rates have been shown to predict seizure outcome, it is not yet clear whether their morphological features might improve this prediction. We validated HFO rates against seizure outcome and delineated the distribution of HFO morphological features. We collected stereo-EEG recordings from 20 patients (231 electrodes; 1,943 contacts). We computed HFO rates (the co-occurrence of ripples and fast ripples) through a validated automated detector during non-rapid eye movement sleep. Applying machine learning, we delineated HFO morphological features within and outside epileptogenic tissue across mesial temporal lobe (MTL) and Neocortex. HFO rates predicted seizure outcome with 85% accuracy, 79% specificity, 100% sensitivity, 100% negative predictive value, and 67% positive predictive value. The analysis of HFO features showed larger amplitude in the epileptogenic tissue, similar morphology for epileptogenic HFO in MTL and Neocortex, and larger amplitude for physiological HFO in MTL. We confirmed HFO rates as a reliable biomarker for epilepsy surgery and characterized the potential clinical relevance of HFO morphological features. Our results support the prospective use of HFO in epilepsy surgery and contribute to the anatomical mapping of HFO morphology.
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Affiliation(s)
- Victor Karpychev
- Center for Language and Brain, HSE University, Moscow, Russia
- *Correspondence: Victor Karpychev,
| | | | - Nikita Utyashev
- National Medical and Surgical Center named after N.I. Pirogov, Moscow, Russia
| | - Nikita Pedyash
- National Medical and Surgical Center named after N.I. Pirogov, Moscow, Russia
| | - Andrey Zuev
- National Medical and Surgical Center named after N.I. Pirogov, Moscow, Russia
| | - Olga Dragoy
- Center for Language and Brain, HSE University, Moscow, Russia
- Institute of Linguistics, Russian Academy of Sciences, Moscow, Russia
| | - Tommaso Fedele
- Institute for Cognitive Neuroscience, HSE University, Moscow, Russia
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McLeod GA, Abbasian P, Toutant D, Ghassemi A, Duke T, Rycyk C, Serletis D, Moussavi Z, Ng MC. Sleep-wake states change the interictal localization of candidate epileptic source generators. Sleep 2022; 45:6547903. [PMID: 35279715 PMCID: PMC9189983 DOI: 10.1093/sleep/zsac062] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/23/2021] [Revised: 02/28/2022] [Indexed: 11/12/2022] Open
Abstract
STUDY OBJECTIVES To compare estimated epileptic source localizations from 5 sleep-wake states (SWS): wakefulness (W), rapid eye movement sleep (REM), and non-REM 1-3. METHODS Electrical source localization (sLORETA) of interictal spikes from different SWS on surface EEG from the epilepsy monitoring unit at spike peak and take-off, with results mapped to individual brain models for 75% of patients. Concordance was defined as source localization voxels shared between 2 and 5 SWS, and discordance as those unique to 1 SWS against 1-4 other SWS. RESULTS 563 spikes from 16 prospectively recruited focal epilepsy patients across 161 day-nights. SWS exerted significant differences at spike peak but not take-off. Source localization size did not vary between SWS. REM localizations were smaller in multifocal than unifocal patients (28.8% vs. 54.4%, p = .0091). All five SWS contributed about 45% of their localizations to converge onto 17.0 ± 15.5% voxels. Against any one other SWS, REM was least concordant (54.4% vs. 66.9%, p = .0006) and most discordant (39.3% vs. 29.6%, p = .0008). REM also yielded the most unique localizations (20.0% vs. 8.6%, p = .0059). CONCLUSIONS REM was best suited to identify candidate epileptic sources. sLORETA proposes a model in which an "omni-concordant core" of source localizations shared by all five SWS is surrounded by a "penumbra" of source localizations shared by some but not all SWS. Uniquely, REM spares this core to "move" source voxels from the penumbra to unique cortex not localized by other SWS. This may reflect differential intra-spike propagation in REM, which may account for its reported superior localizing abilities.
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Affiliation(s)
- Graham A McLeod
- Department of Clinical Neurosciences, University of Calgary, Calgary, AB, Canada
| | - Parandoush Abbasian
- Medical Physics, Department of Physics and Astronomy, University of Manitoba, Winnipeg, MB, Canada.,CancerCare Manitoba Research Institute, Winnipeg, MB, Canada
| | - Darion Toutant
- Biomedical Engineering, University of Manitoba, Winnipeg, MB, Canada
| | | | - Tyler Duke
- Biomedical Engineering, University of Manitoba, Winnipeg, MB, Canada
| | - Conrad Rycyk
- Biomedical Engineering, University of Manitoba, Winnipeg, MB, Canada
| | - Demitre Serletis
- Charles Shor Epilepsy Center, Cleveland Clinic, Cleveland, OH, USA.,Department of Neurosurgery, Cleveland Clinic Foundation, Cleveland, OH, USA
| | - Zahra Moussavi
- Biomedical Engineering, University of Manitoba, Winnipeg, MB, Canada
| | - Marcus C Ng
- Biomedical Engineering, University of Manitoba, Winnipeg, MB, Canada.,Section of Neurology, University of Manitoba, Winnipeg, MB, Canada
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8
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Arslan GA, Saygi S, Bodur E, Cicek C, Tezer FI. Relation between orexin A and epileptic seizures. Epilepsy Res 2022; 184:106972. [DOI: 10.1016/j.eplepsyres.2022.106972] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/07/2021] [Revised: 02/23/2022] [Accepted: 06/22/2022] [Indexed: 11/19/2022]
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Ali R, Gollwitzer S, Reindl C, Hamer H, Coras R, Blümcke I, Buchfelder M, Hastreiter P, Rampp S. Phase-Amplitude Coupling measures for determination of the epileptic network: A methodological comparison. J Neurosci Methods 2022; 370:109484. [DOI: 10.1016/j.jneumeth.2022.109484] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/05/2021] [Revised: 12/29/2021] [Accepted: 01/18/2022] [Indexed: 12/01/2022]
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10
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Numata-Uematsu Y, Uematsu M, Sakuraba R, Iwasaki M, Osawa S, Jin K, Nakasato N, Kure S. The Onset of Interictal Spike-Related Ripples Facilitates Detection of the Epileptogenic Zone. Front Neurol 2021; 12:724417. [PMID: 34803874 PMCID: PMC8599368 DOI: 10.3389/fneur.2021.724417] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/13/2021] [Accepted: 10/14/2021] [Indexed: 11/13/2022] Open
Abstract
Objective: Accurate estimation of the epileptogenic zone (EZ) is essential for favorable outcomes in epilepsy surgery. Conventional ictal electrocorticography (ECoG) onset is generally used to detect the EZ but is insufficient in achieving seizure-free outcomes. By contrast, high-frequency oscillations (HFOs) could be useful markers of the EZ. Hence, we aimed to detect the EZ using interictal spikes and investigated whether the onset area of interictal spike-related HFOs was within the EZ. Methods: The EZ is considered to be included in the resection area among patients with seizure-free outcomes after surgery. Using a complex demodulation technique, we developed a method to determine the onset channels of interictal spike-related ripples (HFOs of 80-200 Hz) and investigated whether they are within the resection area. Results: We retrospectively examined 12 serial patients who achieved seizure-free status after focal resection surgery. Using the method that we developed, we determined the onset channels of interictal spike-related ripples and found that for all 12 patients, they were among the resection channels. The onset frequencies of ripples were in the range of 80-150 Hz. However, the ictal onset channels (evaluated based on ictal ECoG patterns) and ripple onset channels coincided in only 3 of 12 patients. Conclusions: Determining the onset area of interictal spike-related ripples could facilitate EZ estimation. This simple method that utilizes interictal ECoG may aid in preoperative evaluation and improve epilepsy surgery outcomes.
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Affiliation(s)
| | - Mitsugu Uematsu
- Department of Pediatrics, Tohoku University School of Medicine, Sendai, Japan
| | - Rie Sakuraba
- Department of Epileptology, Tohoku University School of Medicine, Sendai, Japan
| | - Masaki Iwasaki
- Department of Neurosurgery, Tohoku University School of Medicine, Sendai, Japan.,Department of Neurosurgery, National Center Hospital of Neurology and Psychiatry, Tokyo, Japan
| | - Shinichiro Osawa
- Department of Neurosurgery, Tohoku University School of Medicine, Sendai, Japan
| | - Kazutaka Jin
- Department of Epileptology, Tohoku University School of Medicine, Sendai, Japan
| | - Nobukazu Nakasato
- Department of Epileptology, Tohoku University School of Medicine, Sendai, Japan
| | - Shigeo Kure
- Department of Pediatrics, Tohoku University School of Medicine, Sendai, Japan
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11
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Ren G, Sun Y, Wang D, Ren J, Dai J, Mei S, Li Y, Wang X, Yang X, Yan J, Wang Q. Identification of Epileptogenic and Non-epileptogenic High-Frequency Oscillations Using a Multi-Feature Convolutional Neural Network Model. Front Neurol 2021; 12:640526. [PMID: 34721249 PMCID: PMC8553964 DOI: 10.3389/fneur.2021.640526] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/11/2020] [Accepted: 09/06/2021] [Indexed: 11/26/2022] Open
Abstract
Accurately identifying epileptogenic zone (EZ) using high-frequency oscillations (HFOs) is a challenge that must be mastered to transfer HFOs into clinical use. We analyzed the ability of a convolutional neural network (CNN) model to distinguish EZ and non-EZ HFOs. Nineteen medically intractable epilepsy patients with good surgical outcomes 2 years after surgery were studied. Five-minute interictal intracranial electroencephalogram epochs of slow-wave sleep were selected randomly. Then 5 s segments of ripples (80–200 Hz) and fast ripples (FRs, 200–500 Hz) were detected automatically. The EZs and non-EZs were identified using the surgery resection range. We innovatively converted all epochs into four types of images using two scales: original waveforms, filtered waveforms, wavelet spectrum images, and smoothed pseudo Wigner–Ville distribution (SPWVD) spectrum images. Two scales were fixed and fitted scales. We then used a CNN model to classify the HFOs into EZ and non-EZ categories. As a result, 7,000 epochs of ripples and 2,000 epochs of FRs were randomly selected from the EZ and non-EZ data for analysis. Our CNN model can distinguish EZ and non-EZ HFOs successfully. Except for original ripple waveforms, the results from CNN models that are trained using fixed-scale images are significantly better than those from models trained using fitted-scale images (p < 0.05). Of the four fixed-scale transformations, the CNN based on the adjusted SPWVD (ASPWVD) produced the best accuracies (80.89 ± 1.43% and 77.85 ± 1.61% for ripples and FRs, respectively, p < 0.05). The CNN using ASPWVD transformation images is an effective deep learning method that can be used to classify EZ and non-EZ HFOs.
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Affiliation(s)
- Guoping Ren
- Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China.,China National Clinical Research Center for Neurological Diseases, Beijing, China
| | - Yueqian Sun
- Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China.,China National Clinical Research Center for Neurological Diseases, Beijing, China.,Collaborative Innovation Center for Brain Disorders, Beijing Institute of Brain Disorders, Capital Medical University, Beijing, China
| | - Dan Wang
- Department of Neurology, Xingtai People's Hospital, Hebei, China
| | - Jiechuan Ren
- Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China.,China National Clinical Research Center for Neurological Diseases, Beijing, China
| | - Jindong Dai
- Department of Functional Neurosurgery, Beijing Haidian Hospital, Beijing, China
| | - Shanshan Mei
- Department of Neurology, Xuanwu Hospital, Capital Medical University, Beijing, China
| | - Yunlin Li
- Department of Neurosurgery, Capital Institute of Pediatrics, Children's Hospital, Beijing, China
| | - Xiaofei Wang
- Department of Neurology, National Center for Children's Health, Beijing Children's Hospital, Capital Medical University, Beijing, China
| | | | - Jiaqing Yan
- College of Electrical and Control Engineering, North China University of Technology, Beijing, China
| | - Qun Wang
- Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China.,China National Clinical Research Center for Neurological Diseases, Beijing, China.,Collaborative Innovation Center for Brain Disorders, Beijing Institute of Brain Disorders, Capital Medical University, Beijing, China
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12
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Ma H, Wang Z, Li C, Chen J, Wang Y. Phase-Amplitude Coupling and Epileptogenic Zone Localization of Frontal Epilepsy Based on Intracranial EEG. Front Neurol 2021; 12:718683. [PMID: 34566860 PMCID: PMC8458805 DOI: 10.3389/fneur.2021.718683] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/01/2021] [Accepted: 08/17/2021] [Indexed: 11/28/2022] Open
Abstract
Objective: This study aimed to explore the characteristics of phase-amplitude coupling in patients with frontal epilepsy based on their electrocorticography data, in order to identify the localization of epileptic regions and further guide clinical resection surgery. Methods: We adopted the modulation index based on the Kullback-Leibler distance, phase-amplitude coupling co-modulogram, and time-varying phase-amplitude modulogram to explore the temporal-spatial patterns and characterization of PAC strength during the period from inter- seizure to post-seizure. Taking the resected area as the gold standard, the epileptogenic zone was located based on MI values of 7 different seizure periods, and the accuracy of localization was measured by the area under the receiver operating curve. Results: (1) The PAC in the inter- and pre-seizure periods was weak and paroxysmal, but strong PAC channels were confined more to the seizure-onset zone and resection region. PAC during the seizure period was intense and persistent, but gradually deviated from the seizure-onset zone. (2) The characteristics of coupling strength of the inter- and pre-seizure EEG can be used to accurately locate the epileptogenic zone, which is better than that in periods after the beginning of a seizure. (3) In an epileptic seizure, the preferred phases of coupling were usually in the rising branches at the pre- and early-seizure stages, while those in the middle- and terminal-seizure were usually in the falling branch. We thus speculate that the coupling occurred in the rising branch can promote the recruitment of abnormal discharge, while the coupling occurred in the falling branch can inhibit the abnormal discharge. Conclusion: The findings suggest that the phase-amplitude coupling during inter- and pre-seizure is a promising marker of epileptic focus location. The preferred phase of coupling changed regularly with the time of epileptic seizure, suggesting that the surge and suppression of abnormal discharges are related to different phases.
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Affiliation(s)
- Huijuan Ma
- Department of Neurology, Xuanwu Hospital, Capital Medical University, Beijing, China
| | - Zeyu Wang
- Department of Biomedical Engineering, Shenyan University of Technology, Shenyang, China
| | - Chunsheng Li
- Department of Biomedical Engineering, Shenyan University of Technology, Shenyang, China
| | - Jia Chen
- Department of Neurology, Xuanwu Hospital, Capital Medical University, Beijing, China.,Beijing Key Laboratory of Neuromodulation, Beijing, China.,Center of Epilepsy, Beijing Institute for Brain Disorders, Capital Medical University, Beijing, China
| | - Yuping Wang
- Department of Neurology, Xuanwu Hospital, Capital Medical University, Beijing, China.,Beijing Key Laboratory of Neuromodulation, Beijing, China.,Center of Epilepsy, Beijing Institute for Brain Disorders, Capital Medical University, Beijing, China
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13
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McCrimmon CM, Riba A, Garner C, Maser AL, Phillips DJ, Steenari M, Shrey DW, Lopour BA. Automated detection of ripple oscillations in long-term scalp EEG from patients with infantile spasms. J Neural Eng 2021; 18. [PMID: 33217752 DOI: 10.1088/1741-2552/abcc7e] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/22/2020] [Accepted: 11/20/2020] [Indexed: 11/11/2022]
Abstract
Objective.Scalp high-frequency oscillations (HFOs) are a promising biomarker of epileptogenicity in infantile spasms (IS) and many other epilepsy syndromes, but prior studies have relied on visual analysis of short segments of data due to the prevalence of artifacts in EEG. Here we set out to robustly characterize the rate and spatial distribution of HFOs in large datasets from IS subjects using fully automated HFO detection techniques.Approach.We prospectively collected long-term scalp EEG data from 12 subjects with IS and 18 healthy controls. For patients with IS, recording began prior to diagnosis and continued through initiation of treatment with adrenocorticotropic hormone (ACTH). The median analyzable EEG duration was 18.2 h for controls and 84.5 h for IS subjects (∼1300 h total). Ripples (80-250 Hz) were detected in all EEG data using an automated algorithm.Main results.HFO rates were substantially higher in patients with IS compared to controls. In IS patients, HFO rates were higher during sleep compared to wakefulness (median 5.5 min-1and 2.9 min-1, respectively;p = 0.002); controls did not exhibit a difference in HFO rate between sleep and wakefulness (median 0.98 min-1and 0.82 min-1, respectively). Spatially, IS patients exhibited significantly higher rates of HFOs in the posterior parasaggital region and significantly lower HFO rates in frontal channels, and this difference was more pronounced during sleep. In IS subjects, ACTH therapy significantly decreased the rate of HFOs.Significance.Here we provide a detailed characterization of the spatial distribution and rates of HFOs associated with IS, which may have relevance for diagnosis and assessment of treatment response. We also demonstrate that our fully automated algorithm can be used to detect HFOs in long-term scalp EEG with sufficient accuracy to clearly discriminate healthy subjects from those with IS.
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Affiliation(s)
- Colin M McCrimmon
- Medical Scientist Training Program, University of California, Irvine, CA 92617, United States of America.,Department Neurology, University of California, Los Angeles, CA 90095, United States of America
| | - Aliza Riba
- Division Neurology, Children's Hospital of Orange County, Orange, CA 92868, United States of America
| | - Cristal Garner
- Division Neurology, Children's Hospital of Orange County, Orange, CA 92868, United States of America
| | - Amy L Maser
- Department Psychology, Children's Hospital of Orange County, Orange, CA 92868, United States of America
| | - Donald J Phillips
- Division Neurology, Children's Hospital of Orange County, Orange, CA 92868, United States of America.,Department Pediatrics, University of California, Irvine, Irvine, CA 92617, United States of America
| | - Maija Steenari
- Division Neurology, Children's Hospital of Orange County, Orange, CA 92868, United States of America.,Department Pediatrics, University of California, Irvine, Irvine, CA 92617, United States of America
| | - Daniel W Shrey
- Division Neurology, Children's Hospital of Orange County, Orange, CA 92868, United States of America.,Department Pediatrics, University of California, Irvine, Irvine, CA 92617, United States of America
| | - Beth A Lopour
- Department Biomedical Engineering, University of California, Irvine, Irvine, CA 92617, United States of America
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14
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Fan Y, Dong L, Liu X, Wang H, Liu Y. Recent advances in the noninvasive detection of high-frequency oscillations in the human brain. Rev Neurosci 2020; 32:305-321. [PMID: 33661582 DOI: 10.1515/revneuro-2020-0073] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/14/2020] [Accepted: 10/23/2020] [Indexed: 01/10/2023]
Abstract
In recent decades, a significant body of evidence based on invasive clinical research has showed that high-frequency oscillations (HFOs) are a promising biomarker for localization of the seizure onset zone (SOZ), and therefore, have the potential to improve postsurgical outcomes in patients with epilepsy. Emerging clinical literature has demonstrated that HFOs can be recorded noninvasively using methods such as scalp electroencephalography (EEG) and magnetoencephalography (MEG). Not only are HFOs considered to be a useful biomarker of the SOZ, they also have the potential to gauge disease severity, monitor treatment, and evaluate prognostic outcomes. In this article, we review recent clinical research on noninvasively detected HFOs in the human brain, with a focus on epilepsy. Noninvasively detected scalp HFOs have been investigated in various types of epilepsy. HFOs have also been studied noninvasively in other pathologic brain disorders, such as migraine and autism. Herein, we discuss the challenges reported in noninvasive HFO studies, including the scarcity of MEG and high-density EEG equipment in clinical settings, low signal-to-noise ratio, lack of clinically approved automated detection methods, and the difficulty in differentiating between physiologic and pathologic HFOs. Additional studies on noninvasive recording methods for HFOs are needed, especially prospective multicenter studies. Further research is fundamental, and extensive work is needed before HFOs can routinely be assessed in clinical settings; however, the future appears promising.
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Affiliation(s)
- Yuying Fan
- Department of Pediatrics, Shengjing Hospital of China Medical University, Shenyang, China
| | - Liping Dong
- Library of China Medical University, Shenyang, China
| | - Xueyan Liu
- Department of Pediatrics, Shengjing Hospital of China Medical University, Shenyang, China
| | - Hua Wang
- Department of Pediatrics, Shengjing Hospital of China Medical University, Shenyang, China
| | - Yunhui Liu
- Department of Neurosurgery, Shengjing Hospital of China Medical University, Shenyang, China
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15
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Wong SM, Arski ON, Workewych AM, Donner E, Ochi A, Otsubo H, Snead OC, Ibrahim GM. Detection of high-frequency oscillations in electroencephalography: A scoping review and an adaptable open-source framework. Seizure 2020; 84:23-33. [PMID: 33271473 DOI: 10.1016/j.seizure.2020.11.009] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/17/2020] [Revised: 11/11/2020] [Accepted: 11/12/2020] [Indexed: 11/19/2022] Open
Abstract
PURPOSE High frequency oscillations (HFOs) are putative biomarkers of epileptogenicity. These electrophysiological phenomena can be effectively detected in electroencephalography using automated methods. Nonetheless, the implementation of these methods into clinical practice remains challenging as significant variability exists between algorithms and their characterizations of HFOs. Here, we perform a scoping review of the literature pertaining to automated HFO detection methods. In addition, we propose a framework for defining and detecting HFOs based on a simplified single-stage time-frequency based detection algorithm with clinically-familiar parameters. METHODS Several databases (OVID Medline, Web of Science, PubMed) were searched for articles presenting novel, automated HFO detection methods. Details related to the algorithm and various stages of data acquisition, pre-processing, and analysis were abstracted from included studies. RESULTS From the 261 records screened, 57 articles presented novel, automated HFO detection methods and were included in the scoping review. These algorithms were categorized into 3 groups based on their most salient features: energy thresholding, time-frequency analysis, and data mining/machine learning. Algorithms were optimized for specific datasets and suffered from low specificity. A framework for user-constrained inputs is proposed to circumvent some of the weaknesses of highly performant detectors. CONCLUSIONS Further efforts are required to optimize and validate existing automated HFO detection methods for clinical utility. The proposed framework may be applied to understand and standardize the variations in HFO definitions across institutions.
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Affiliation(s)
- Simeon M Wong
- Program in Neuroscience and Mental Health, Hospital for Sick Children Research Institute, Toronto, Canada; Institute of Biomedical Engineering, University of Toronto, Toronto, Canada
| | - Olivia N Arski
- Program in Neuroscience and Mental Health, Hospital for Sick Children Research Institute, Toronto, Canada; Institute of Medical Science, University of Toronto, Toronto, Canada
| | - Adriana M Workewych
- Program in Neuroscience and Mental Health, Hospital for Sick Children Research Institute, Toronto, Canada; Faculty of Medicine, University of Toronto, Toronto, Canada
| | - Elizabeth Donner
- Division of Neurology, Hospital for Sick Children, Toronto, Canada
| | - Ayako Ochi
- Division of Neurology, Hospital for Sick Children, Toronto, Canada
| | - Hiroshi Otsubo
- Division of Neurology, Hospital for Sick Children, Toronto, Canada
| | - O Carter Snead
- Division of Neurology, Hospital for Sick Children, Toronto, Canada
| | - George M Ibrahim
- Program in Neuroscience and Mental Health, Hospital for Sick Children Research Institute, Toronto, Canada; Institute of Biomedical Engineering, University of Toronto, Toronto, Canada; Institute of Medical Science, University of Toronto, Toronto, Canada; Division of Neurosurgery, Hospital for Sick Children, Department of Surgery, University of Toronto, Toronto, Canada.
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16
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Pail M, Cimbálník J, Roman R, Daniel P, Shaw DJ, Chrastina J, Brázdil M. High frequency oscillations in epileptic and non-epileptic human hippocampus during a cognitive task. Sci Rep 2020; 10:18147. [PMID: 33097749 PMCID: PMC7585420 DOI: 10.1038/s41598-020-74306-3] [Citation(s) in RCA: 18] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/27/2019] [Accepted: 09/23/2020] [Indexed: 12/04/2022] Open
Abstract
Hippocampal high-frequency electrographic activity (HFOs) represents one of the major discoveries not only in epilepsy research but also in cognitive science over the past few decades. A fundamental challenge, however, has been the fact that physiological HFOs associated with normal brain function overlap in frequency with pathological HFOs. We investigated the impact of a cognitive task on HFOs with the aim of improving differentiation between epileptic and non-epileptic hippocampi in humans. Hippocampal activity was recorded with depth electrodes in 15 patients with focal epilepsy during a resting period and subsequently during a cognitive task. HFOs in ripple and fast ripple frequency ranges were evaluated in both conditions, and their rate, spectral entropy, relative amplitude and duration were compared in epileptic and non-epileptic hippocampi. The similarity of HFOs properties recorded at rest in epileptic and non-epileptic hippocampi suggests that they cannot be used alone to distinguish between hippocampi. However, both ripples and fast ripples were observed with higher rates, higher relative amplitudes and longer durations at rest as well as during a cognitive task in epileptic compared with non-epileptic hippocampi. Moreover, during a cognitive task, significant reductions of HFOs rates were found in epileptic hippocampi. These reductions were not observed in non-epileptic hippocampi. Our results indicate that although both hippocampi generate HFOs with similar features that probably reflect non-pathological phenomena, it is possible to differentiate between epileptic and non-epileptic hippocampi using a simple odd-ball task.
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Affiliation(s)
- Martin Pail
- First Department of Neurology, Brno Epilepsy Center (Full member of the ERN EpiCARE), St. Anne's University Hospital and Medical Faculty of Masaryk University, Pekařská 53, Brno, 65691, Czech Republic.
| | - Jan Cimbálník
- International Clinical Research Center, St. Anne's University Hospital, Brno, Czech Republic
| | - Robert Roman
- First Department of Neurology, Brno Epilepsy Center (Full member of the ERN EpiCARE), St. Anne's University Hospital and Medical Faculty of Masaryk University, Pekařská 53, Brno, 65691, Czech Republic.,CEITEC - Central European Institute of Technology, Masaryk University, Brno, Czech Republic
| | - Pavel Daniel
- First Department of Neurology, Brno Epilepsy Center (Full member of the ERN EpiCARE), St. Anne's University Hospital and Medical Faculty of Masaryk University, Pekařská 53, Brno, 65691, Czech Republic.,CEITEC - Central European Institute of Technology, Masaryk University, Brno, Czech Republic
| | - Daniel J Shaw
- CEITEC - Central European Institute of Technology, Masaryk University, Brno, Czech Republic.,School of Life and Health Sciences, Aston University, Birmingham, UK
| | - Jan Chrastina
- Department of Neurosurgery, Brno Epilepsy Center, St. Anne's University Hospital and Medical Faculty of Masaryk University, Brno, Czech Republic
| | - Milan Brázdil
- First Department of Neurology, Brno Epilepsy Center (Full member of the ERN EpiCARE), St. Anne's University Hospital and Medical Faculty of Masaryk University, Pekařská 53, Brno, 65691, Czech Republic.,CEITEC - Central European Institute of Technology, Masaryk University, Brno, Czech Republic
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17
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Okamura A, Otsubo H, Hashizume A, Kagawa K, Katagiri M, Seyama G, Kurisu K, Iida K. Secondary epileptogenesis on gradient magnetic-field topography correlates with seizure outcomes after vagus nerve stimulation. Epilepsy Res 2020; 167:106463. [PMID: 32987243 DOI: 10.1016/j.eplepsyres.2020.106463] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/06/2020] [Revised: 08/07/2020] [Accepted: 09/07/2020] [Indexed: 11/26/2022]
Abstract
OBJECTIVE To determine the correlation between secondary unilateral or bilateral spreading on gradient magnetic-field topography (GMFT) before and after vagus nerve stimulation (VNS), and postoperative seizure outcomes. METHODS We analyzed pre- and post-VNS magnetoencephalography (MEG) in 15 patients with VNS implants. We applied McHugh classification to evaluate seizure outcomes. GMFT visualized the spatiotemporal spread of the gradient magnetic field from MEG (>300 fT/cm) before and after the spike peak. We compared the proportion of bilaterally spreading (PBS) MEG spikes and seizure outcomes. We also compared the interhemispheric time difference (ITD) between patients with and without corpus callosotomy. RESULTS We allocated patients with favorable seizure outcomes of class I and II to group A (9 patients) and poor outcomes of class III-V to group B (6 patients). The number of post-VNS MEG spikes was significantly reduced compared to pre-VNS MEG spikes in group A, but not in group B. Group A showed significantly higher preoperative PBS than group B. Postoperative ITD significantly decreased in 5 patients who underwent corpus callosotomy compared to 10 patients without. CONCLUSION GMFT can detect the inter- and intrahemispheric spreading of spikes with high spatiotemporal resolution on the brain surface. Frequent interictal MEG spikes propagating bilaterally on GMFT may reflect a favorable seizure outcome after VNS. GMFT can identify dependent secondary epileptogenic spikes responding to VNS, which may be used to control generalized seizures in a subset of patients with pharmaco-resistant epilepsy.
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Affiliation(s)
- Akitake Okamura
- Department of Neurosurgery, Graduate School of Biomedical and Health Sciences, Hiroshima University, Hiroshima, Japan; Epilepsy Center, Hiroshima University Hospital, Hiroshima, Japan
| | - Hiroshi Otsubo
- Division of Neurology, Department of Pediatrics, The Hospital for Sick Children, Toronto, Canada
| | - Akira Hashizume
- Department of Neurosurgery, Graduate School of Biomedical and Health Sciences, Hiroshima University, Hiroshima, Japan; Epilepsy Center, Hiroshima University Hospital, Hiroshima, Japan
| | - Kota Kagawa
- Department of Neurosurgery, Graduate School of Biomedical and Health Sciences, Hiroshima University, Hiroshima, Japan; Epilepsy Center, Hiroshima University Hospital, Hiroshima, Japan
| | - Masaya Katagiri
- Department of Neurosurgery, Graduate School of Biomedical and Health Sciences, Hiroshima University, Hiroshima, Japan; Epilepsy Center, Hiroshima University Hospital, Hiroshima, Japan
| | - Go Seyama
- Department of Neurosurgery, Graduate School of Biomedical and Health Sciences, Hiroshima University, Hiroshima, Japan; Epilepsy Center, Hiroshima University Hospital, Hiroshima, Japan
| | - Kaoru Kurisu
- Department of Neurosurgery, Chugoku Rosai Hospital, Hiroshima, Japan
| | - Koji Iida
- Department of Neurosurgery, Graduate School of Biomedical and Health Sciences, Hiroshima University, Hiroshima, Japan; Epilepsy Center, Hiroshima University Hospital, Hiroshima, Japan.
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18
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Ren G, Yan J, Sun Y, Ren J, Dai J, Mei S, Li Y, Wang X, Yang X, Wang Q. Association Between Interictal High-Frequency Oscillations and Slow Wave in Refractory Focal Epilepsy With Good Surgical Outcome. Front Hum Neurosci 2020; 14:335. [PMID: 33005137 PMCID: PMC7479180 DOI: 10.3389/fnhum.2020.00335] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/07/2020] [Accepted: 07/29/2020] [Indexed: 11/13/2022] Open
Abstract
High-frequency oscillations (HFOs) have been proposed as a promising biomarker of the epileptogenic zone (EZ). But accurate delineation of EZ based on HFOs is still challenging. Our study compared HFOs from EZ and non-EZ on the basis of their associations with interictal slow waves, aiming at exploring a new way to localize EZ. Nineteen medically intractable epilepsy patients with good surgical outcome were included. Five minute interictal intracranial electroencephalography (EEG) epochs of slow-wave sleep were randomly selected; then ripples (80–200 Hz), fast ripples (FRs; 200–500 Hz), and slow waves (0.1–4 Hz) were automatically analyzed. The EZ and non-EZ were identified by resection range during the surgeries. We found that both ripples and FRs superimposed more frequently on slow waves in EZ than in non-EZ (P < 0.01). Although ripples preferred to occur on the down state of slow waves in both two groups, ripples in EZ tended to be closer to the down-state peak of slow wave than in non-EZ (-174 vs. -231 ms, P = 0.008). As for FR, no statistical difference was found between the two groups (P = 0.430). Additionally, slow wave-containing ripples in EZ had a steeper slope (1.7 vs. 1.5 μV/ms, P < 0.001) and wider distribution ratio (32.3 vs. 30.1%, P < 0.001) than those in the non-EZ. But for slow wave-containing FR, only a steeper slope (1.7 vs. 1.4 μV/ms, P < 0.001) was observed. Our study innovatively compared the different features of association between HFOs and slow wave in EZ and non-EZ from refractory focal epilepsy with good surgical outcome, proposing a new method to localize EZ and facilitating the surgical plan.
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Affiliation(s)
- Guoping Ren
- Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China.,China National Clinical Research Center for Neurological Diseases, Beijing, China
| | - Jiaqing Yan
- College of Electrical and Control Engineering, North China University of Technology, Beijing, China
| | - Yueqian Sun
- Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China.,China National Clinical Research Center for Neurological Diseases, Beijing, China.,Laboratory of Brain Disorders, Collaborative Innovation Center for Brain Disorders, Beijing Institute of Brain Disorders, Capital Medical University, Ministry of Science and Technology, Beijing, China
| | - Jiechuan Ren
- Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China.,China National Clinical Research Center for Neurological Diseases, Beijing, China
| | - Jindong Dai
- Department of Functional Neurosurgery, Beijing Haidian Hospital, Beijing, China
| | - Shanshan Mei
- Department of Functional Neurosurgery, Beijing Haidian Hospital, Beijing, China
| | - Yunlin Li
- Department of Functional Neurosurgery, Beijing Haidian Hospital, Beijing, China
| | - Xiaofei Wang
- Department of Functional Neurosurgery, Beijing Haidian Hospital, Beijing, China
| | - Xiaofeng Yang
- Laboratory of Brain Disorders, Collaborative Innovation Center for Brain Disorders, Beijing Institute of Brain Disorders, Capital Medical University, Ministry of Science and Technology, Beijing, China.,Neuroelectrophysiological Laboratory, Xuanwu Hospital, Capital Medical University, Beijing, China.,Guangzhou Regenerative Medicine and Health Guangdong Laboratory, Guangzhou, China
| | - Qun Wang
- Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China.,China National Clinical Research Center for Neurological Diseases, Beijing, China.,Laboratory of Brain Disorders, Collaborative Innovation Center for Brain Disorders, Beijing Institute of Brain Disorders, Capital Medical University, Ministry of Science and Technology, Beijing, China
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19
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Nevalainen P, von Ellenrieder N, Klimeš P, Dubeau F, Frauscher B, Gotman J. Association of fast ripples on intracranial EEG and outcomes after epilepsy surgery. Neurology 2020; 95:e2235-e2245. [PMID: 32753439 DOI: 10.1212/wnl.0000000000010468] [Citation(s) in RCA: 21] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/16/2019] [Accepted: 05/12/2020] [Indexed: 01/16/2023] Open
Abstract
OBJECTIVE To examine whether fast ripples (FRs) are an accurate marker of the epileptogenic zone, we analyzed overnight stereo-EEG recordings from 43 patients and hypothesized that FR resection ratio, maximal FR rate, and FR distribution predict postsurgical seizure outcome. METHODS We detected FRs automatically from an overnight recording edited for artifacts and visually from a 5-minute period of slow-wave sleep. We examined primarily the accuracy of removing ≥50% of total FR events or of channels with FRs to predict postsurgical seizure outcome (Engel class I = good, classes II-IV = poor) according to the whole-night and 5-minute analysis approaches. Secondarily, we examined the association of low overall FR rates or absence or incomplete resection of 1 dominant FR area with poor outcome. RESULTS The accuracy of outcome prediction was highest (81%, 95% confidence interval [CI] 67%-92%) with the use of the FR event resection ratio and whole-night recording (vs 72%, 95% CI 56%-85%, for the visual 5-minute approach). Absence of channels with FR rates >6/min (p = 0.001) and absence or incomplete resection of 1 dominant FR area (p < 0.001) were associated with poor outcome. CONCLUSIONS FRs are accurate in predicting epilepsy surgery outcome at the individual level when overnight recordings are used. Absence of channels with high FR rates or absence of 1 dominant FR area is a poor prognostic factor that may reflect suboptimal spatial sampling of the epileptogenic zone or multifocality, rather than an inherently low sensitivity of FRs. CLASSIFICATION OF EVIDENCE This study provides Class II evidence that FRs are accurate in predicting epilepsy surgery outcome.
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Affiliation(s)
- Päivi Nevalainen
- From the Montreal Neurological Institute and Hospital (P.N., N.v.E., P.K., F.D., B.F., J.G.), McGill University, Quebec, Canada; and Department of Clinical Neurophysiology (P.N.), Children´s Hospital, HUS Medical Imaging Center, University of Helsinki and Helsinki University Hospital, Finland.
| | - Nicolás von Ellenrieder
- From the Montreal Neurological Institute and Hospital (P.N., N.v.E., P.K., F.D., B.F., J.G.), McGill University, Quebec, Canada; and Department of Clinical Neurophysiology (P.N.), Children´s Hospital, HUS Medical Imaging Center, University of Helsinki and Helsinki University Hospital, Finland
| | - Petr Klimeš
- From the Montreal Neurological Institute and Hospital (P.N., N.v.E., P.K., F.D., B.F., J.G.), McGill University, Quebec, Canada; and Department of Clinical Neurophysiology (P.N.), Children´s Hospital, HUS Medical Imaging Center, University of Helsinki and Helsinki University Hospital, Finland
| | - François Dubeau
- From the Montreal Neurological Institute and Hospital (P.N., N.v.E., P.K., F.D., B.F., J.G.), McGill University, Quebec, Canada; and Department of Clinical Neurophysiology (P.N.), Children´s Hospital, HUS Medical Imaging Center, University of Helsinki and Helsinki University Hospital, Finland
| | - Birgit Frauscher
- From the Montreal Neurological Institute and Hospital (P.N., N.v.E., P.K., F.D., B.F., J.G.), McGill University, Quebec, Canada; and Department of Clinical Neurophysiology (P.N.), Children´s Hospital, HUS Medical Imaging Center, University of Helsinki and Helsinki University Hospital, Finland
| | - Jean Gotman
- From the Montreal Neurological Institute and Hospital (P.N., N.v.E., P.K., F.D., B.F., J.G.), McGill University, Quebec, Canada; and Department of Clinical Neurophysiology (P.N.), Children´s Hospital, HUS Medical Imaging Center, University of Helsinki and Helsinki University Hospital, Finland
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20
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McLeod GA, Ghassemi A, Ng MC. Can REM Sleep Localize the Epileptogenic Zone? A Systematic Review and Analysis. Front Neurol 2020; 11:584. [PMID: 32793089 PMCID: PMC7393443 DOI: 10.3389/fneur.2020.00584] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/01/2020] [Accepted: 05/20/2020] [Indexed: 12/31/2022] Open
Abstract
Epilepsy is a common and debilitating neurological disease. When medication cannot control seizures in up to 40% of cases, surgical resection of epileptogenic tissue is a clinically and cost- effective therapy to achieve seizure freedom. To simultaneously resect minimal yet sufficient cortex, exquisite localization of the epileptogenic zone (EZ) is crucial. However, localization is not straightforward, given relative difficulty of capturing seizures, constraints of the inverse problem in source localization, and possible disparate locations of symptomatogenic vs. epileptogenic regions. Thus, attention has been paid to which state of vigilance best localizes the EZ, in the hopes that one or another sleep-wake state may hold the key to improved accuracy of localization. Studies investigating this topic have employed diverse methodologies and produced diverse results. Nonetheless, rapid eye movement sleep (REM) has emerged as a promising sleep-wake state, as epileptic phenomena captured in REM may spatially correspond more closely to the EZ. Cortical neuronal asynchrony in REM may spatially constrain epileptic phenomena to reduce propagation away from the source generator, rendering them of high localizing value. However, some recent work demonstrates best localization in sleep-wake states other than REM, and there are reports of REM providing clearly false localization. Moreover, synchronistic properties and basic mechanisms of human REM remain to be fully characterized. Amidst these uncertainties, there is an urgent need for recording and analytical techniques to improve accuracy of localization. Here we present a systematic review and quantitative analysis of pertinent literature on whether and how REM may help localize epileptogenic foci. To help streamline and accelerate future work on the intriguing anti-epileptic properties of REM, we also introduce a simple, conceptually clear set-theoretic framework to conveniently and rigorously describe the spatial properties of epileptic phenomena in the brain.
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Affiliation(s)
- Graham A McLeod
- Department of Clinical Neurosciences, University of Calgary, Calgary, AB, Canada
| | | | - Marcus C Ng
- Biomedical Engineering, University of Manitoba, Winnipeg, MB, Canada.,Section of Neurology, Department of Internal Medicine, University of Manitoba, Winnipeg, MB, Canada
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Remick M, Ibrahim GM, Mansouri A, Abel TJ. Patient phenotypes and clinical outcomes in invasive monitoring for epilepsy: An individual patient data meta-analysis. Epilepsy Behav 2020; 102:106652. [PMID: 31770717 DOI: 10.1016/j.yebeh.2019.106652] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/09/2019] [Revised: 10/16/2019] [Accepted: 10/17/2019] [Indexed: 12/18/2022]
Abstract
OBJECTIVE Invasive monitoring provides valuable clinical information in patients with drug-resistant epilepsy (DRE). However, there is no clear evidence indicating either stereoelectroencephalography (SEEG) or subdural electrodes (SDE) as the optimal method. Our goal was to examine differences in postresection seizure freedom rates between SEEG- and SDE-informed resective epilepsy surgeries. Additionally, we aimed to determine potential clinical indicators for SEEG or SDE monitoring in patients with drug-resistant epilepsy. METHODS A systematic literature review was performed in which we searched for primary articles using keywords such as "electroencephalography", "intracranial grid", and "epilepsy." Only studies containing individual patient data (IPD) were included for analysis. A one-stage IPD meta-analysis was performed to determine differences in rates of seizure freedom (International League Against Epilepsy (ILAE) guidelines and Engel classification) and resection status between SEEG and SDE patients. A Cox proportional-hazards regression was performed to determine the effect of time on seizure freedom status. Additionally, a principal component analysis was performed to investigate primary drivers of variance between these two groups. RESULTS This IPD meta-analysis compared differences between SEEG and SDE invasive monitoring techniques in 595 patients from 33 studies. Our results demonstrate that while there was no difference in seizure freedom rates regardless of resection (p = 0.0565), SEEG was associated with a lower rate of resection compared with SDE (82.00% SEEG, 92.74% SDE, p = 0.0002). Additionally, while SDE was associated with a higher rate of postresection seizure freedom (54.04% SEEG, 64.32% SDE, p = 0.0247), the difference between seizure freedom rates following SEEG- or SDE-informed resection decreased with long-term follow-up. A principal component analysis showed that cases resulting in SEEG were associated with lower risk of morbidity than SDE cases, which were strongly collinear with multiple subpial transections, anterior temporal lobectomy, amygdalectomy, and hippocampectomy. SIGNIFICANCE In this IPD meta-analysis of SEEG and SDE invasive monitoring techniques, SEEG and SDE were associated with similar rates of seizure freedom at latest follow-up. The former was associated with lower rates of resection. Furthermore, the clinical phenotypes of patients undergoing SEEG monitoring was associated with lower rates of complications. Future long-term prospective registries of IPD are promising options for clarifying the differences in these intracranial monitoring techniques as well as the unique patient phenotypes that may be associated with their indication.
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Affiliation(s)
- Madison Remick
- Department of Neurological Surgery, University of Pittsburgh, Pittsburgh, PA, USA
| | - George M Ibrahim
- Division of Neurosurgery, Department of Surgery, University of Toronto, Toronto, Canada; Division of Neurosurgery, Hospital for Sick Children, Program in Neuroscience and Mental Health, Hospital for Sick Children Research Institute, Toronto, Canada
| | - Alireza Mansouri
- Department of Neurosurgery, Penn State University, Hershey, PA, USA
| | - Taylor J Abel
- Department of Neurological Surgery, University of Pittsburgh, Pittsburgh, PA, USA; Department of Bioengineering, University of Pittsburgh, Pittsburgh, PA, USA.
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Motoi H, Jeong JW, Juhász C, Miyakoshi M, Nakai Y, Sugiura A, Luat AF, Sood S, Asano E. Quantitative analysis of intracranial electrocorticography signals using the concept of statistical parametric mapping. Sci Rep 2019; 9:17385. [PMID: 31758022 PMCID: PMC6874664 DOI: 10.1038/s41598-019-53749-3] [Citation(s) in RCA: 22] [Impact Index Per Article: 4.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/03/2019] [Accepted: 11/04/2019] [Indexed: 11/23/2022] Open
Abstract
Statistical parametric mapping (SPM) is a technique with which one can delineate brain activity statistically deviated from the normative mean, and has been commonly employed in noninvasive neuroimaging and EEG studies. Using the concept of SPM, we developed a novel technique for quantification of the statistical deviation of an intracranial electrocorticography (ECoG) measure from the nonepileptic mean. We validated this technique using data previously collected from 123 patients with drug-resistant epilepsy who underwent resective epilepsy surgery. We determined how the measurement of statistical deviation of modulation index (MI) from the non-epileptic mean (rated by z-score) improved the performance of seizure outcome classification model solely based on conventional clinical, seizure onset zone (SOZ), and neuroimaging variables. Here, MI is a summary measure quantifying the strength of in-situ coupling between high-frequency activity at >150 Hz and slow wave at 3-4 Hz. We initially generated a normative MI atlas showing the mean and standard deviation of slow-wave sleep MI of neighboring non-epileptic channels of 47 patients, whose ECoG sampling involved all four lobes. We then calculated 'MI z-score' at each electrode site. SOZ had a greater 'MI z-score' compared to non-SOZ in the remaining 76 patients. Subsequent multivariate logistic regression analysis and receiver operating characteristic analysis to the combined data of all patients revealed that the full regression model incorporating all predictor variables, including SOZ and 'MI z-score', best classified the seizure outcome with sensitivity/specificity of 0.86/0.76. The model excluding 'MI z-score' worsened its sensitivity/specificity to 0.86/0.48. Furthermore, the leave-one-out analysis successfully cross-validated the full regression model. Measurement of statistical deviation of MI from the non-epileptic mean on invasive recording is technically feasible. Our analytical technique can be used to evaluate the utility of ECoG biomarkers in epilepsy presurgical evaluation.
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Affiliation(s)
- Hirotaka Motoi
- Department of Pediatrics, Children's Hospital of Michigan, Wayne State University, Detroit Medical Center, Detroit, MI, 48201, USA
- Department of Pediatrics, Yokohama City University Medical Center, Yokohama, 2320024, Japan
| | - Jeong-Won Jeong
- Department of Pediatrics, Children's Hospital of Michigan, Wayne State University, Detroit Medical Center, Detroit, MI, 48201, USA
- Department of Neurology, Children's Hospital of Michigan, Wayne State University, Detroit Medical Center, Detroit, MI, 48201, USA
| | - Csaba Juhász
- Department of Pediatrics, Children's Hospital of Michigan, Wayne State University, Detroit Medical Center, Detroit, MI, 48201, USA
- Department of Neurology, Children's Hospital of Michigan, Wayne State University, Detroit Medical Center, Detroit, MI, 48201, USA
- Department of Neurosurgery, Children's Hospital of Michigan, Wayne State University, Detroit Medical Center, Detroit, MI, 48201, USA
| | - Makoto Miyakoshi
- Swartz Center for Computational Neuroscience, Institute for Neural Computation, University of California San Diego, La Jolla, CA, 92093, USA
| | - Yasuo Nakai
- Department of Pediatrics, Children's Hospital of Michigan, Wayne State University, Detroit Medical Center, Detroit, MI, 48201, USA
| | - Ayaka Sugiura
- Department of Pediatrics, Children's Hospital of Michigan, Wayne State University, Detroit Medical Center, Detroit, MI, 48201, USA
| | - Aimee F Luat
- Department of Pediatrics, Children's Hospital of Michigan, Wayne State University, Detroit Medical Center, Detroit, MI, 48201, USA
- Department of Neurology, Children's Hospital of Michigan, Wayne State University, Detroit Medical Center, Detroit, MI, 48201, USA
| | - Sandeep Sood
- Department of Neurosurgery, Children's Hospital of Michigan, Wayne State University, Detroit Medical Center, Detroit, MI, 48201, USA
| | - Eishi Asano
- Department of Pediatrics, Children's Hospital of Michigan, Wayne State University, Detroit Medical Center, Detroit, MI, 48201, USA.
- Department of Neurology, Children's Hospital of Michigan, Wayne State University, Detroit Medical Center, Detroit, MI, 48201, USA.
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Klimes P, Cimbalnik J, Brazdil M, Hall J, Dubeau F, Gotman J, Frauscher B. NREM sleep is the state of vigilance that best identifies the epileptogenic zone in the interictal electroencephalogram. Epilepsia 2019; 60:2404-2415. [PMID: 31705527 DOI: 10.1111/epi.16377] [Citation(s) in RCA: 38] [Impact Index Per Article: 7.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/13/2019] [Revised: 10/09/2019] [Accepted: 10/09/2019] [Indexed: 01/26/2023]
Abstract
OBJECTIVE Interictal epileptiform anomalies such as epileptiform discharges or high-frequency oscillations show marked variations across the sleep-wake cycle. This study investigates which state of vigilance is the best to localize the epileptogenic zone (EZ) in interictal intracranial electroencephalography (EEG). METHODS Thirty patients with drug-resistant epilepsy undergoing stereo-EEG (SEEG)/sleep recording and subsequent open surgery were included; 13 patients (43.3%) had good surgical outcome (Engel class I). Sleep was scored following standard criteria. Multiple features based on the interictal EEG (interictal epileptiform discharges, high-frequency oscillations, univariate and bivariate features) were used to train a support vector machine (SVM) model to classify SEEG contacts placed in the EZ. The performance of the algorithm was evaluated by the mean area under the receiver-operating characteristic (ROC) curves (AUCs) and positive predictive values (PPVs) across 10-minute sections of wake, non-rapid eye movement sleep (NREM) stages N2 and N3, REM sleep, and their combination. RESULTS Highest AUCs were achieved in NREM sleep stages N2 and N3 compared to wakefulness and REM (P < .01). There was no improvement when using a combination of all four states (P > .05); the best performing features in the combined state were selected from NREM sleep. There were differences between good (Engel I) and poor (Engel II-IV) outcomes in PPV (P < .05) and AUC (P < .01) across all states. The SVM multifeature approach outperformed spikes and high-frequency oscillations (P < .01) and resulted in results similar to those of the seizure-onset zone (SOZ; P > .05). SIGNIFICANCE Sleep improves the localization of the EZ with best identification obtained in NREM sleep stages N2 and N3. Results based on the multifeature classification in 10 minutes of NREM sleep were not different from the results achieved by the SOZ based on 12.7 days of seizure monitoring. This finding might ultimately result in a more time-efficient intracranial presurgical investigation of focal epilepsy.
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Affiliation(s)
- Petr Klimes
- Montreal Neurological Institute and Hospital, McGill University, Montréal, Quebec, Canada.,Institute of Scientific Instruments, The Czech Academy of Sciences, Brno, Czech Republic
| | - Jan Cimbalnik
- International Clinical Research Center, St. Anne's University Hospital, Brno, Czech Republic
| | - Milan Brazdil
- Brno Epilepsy Center, Department of Neurology, St. Anne's University Hospital, Faculty of Medicine, Masaryk University, Brno, Czech Republic.,Behavioral and Social Neuroscience Research Group, CEITEC Central European Institute of Technology, Masaryk University, Brno, Czech Republic
| | - Jeffery Hall
- Montreal Neurological Institute and Hospital, McGill University, Montréal, Quebec, Canada
| | - François Dubeau
- Montreal Neurological Institute and Hospital, McGill University, Montréal, Quebec, Canada
| | - Jean Gotman
- Montreal Neurological Institute and Hospital, McGill University, Montréal, Quebec, Canada
| | - Birgit Frauscher
- Montreal Neurological Institute and Hospital, McGill University, Montréal, Quebec, Canada
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Sudhakar SK, Ahmed OJ. More Is More: Potential Benefits of Characterizing High-Frequency Activity Over Long Durations. Epilepsy Curr 2019; 19:397-399. [PMID: 31526032 PMCID: PMC6891179 DOI: 10.1177/1535759719875469] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022] Open
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Yan H, Katz JS, Anderson M, Mansouri A, Remick M, Ibrahim GM, Abel TJ. Method of invasive monitoring in epilepsy surgery and seizure freedom and morbidity: A systematic review. Epilepsia 2019; 60:1960-1972. [PMID: 31423575 DOI: 10.1111/epi.16315] [Citation(s) in RCA: 53] [Impact Index Per Article: 10.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/24/2019] [Revised: 07/23/2019] [Accepted: 07/23/2019] [Indexed: 11/29/2022]
Abstract
OBJECTIVE Invasive monitoring is sometimes necessary to guide resective surgery in epilepsy patients, but the ideal method is unknown. In this systematic review, we assess the association of postresection seizure freedom and adverse events in stereoelectroencephalography (SEEG) and subdural electrodes (SDE). METHODS We searched three electronic databases (MEDLINE, Embase, and CENTRAL [Cochrane Central Register of Controlled Trials]) from their inception to January 2018 with the keywords "electroencephalography," "intracranial grid," and "epilepsy." Studies that presented primary quantitative patient data for postresection seizure freedom with at least 1 year of follow-up or complication rates of SEEG- or SDE-monitored patients were included. Two trained investigators independently collected data from eligible studies. Weighted mean differences (WMDs) with 95% confidence interval (CIs) were used as a measure of the association of SEEG or SDE with seizure freedom and with adverse event outcomes. RESULTS Of 11 462 screened records, 48 studies met inclusion criteria. These studies reported on 1973 SEEG patients and 2036 SDE patients. Our systematic review revealed SEEG was associated with 61.0% and SDE was associated with 56.4% seizure freedom after resection (WMD = +5.8%, 95% CI = 4.7-6.9%, P = .001). Furthermore, SEEG was associated with 4.8% and SDE was associated with 15.5% morbidity (WMD = -10.6%, 95% CI = -11.6 to -9.6%, P = .001). SEEG was associated with 0.2% mortality and SDE was associated with 0.4% mortality (WMD = -0.2%, 95% CI = -0.3 to -0.1%, P = .001). SIGNIFICANCE In this systematic review of SEEG and SDE invasive monitoring techniques, SEEG was associated with fewer surgical resections yet better seizure freedom outcomes in those undergoing resections. SEEG was also associated with lower mortality and morbidity than SDE. Clinical studies directly comparing these modalities are necessary to understand the relative rates of seizure freedom, morbidity, and mortality associated with these techniques.
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Affiliation(s)
- Han Yan
- Division of Neurosurgery, Department of Surgery, University of Toronto, Toronto, Ontario, Canada
| | - Joel S Katz
- Department of Neurological Surgery, University of Pittsburgh, Pittsburgh, Pennsylvania
| | - Melanie Anderson
- Library and Information Services, University Health Network, University of Toronto, Toronto, Ontario, Canada
| | - Alireza Mansouri
- Division of Neurosurgery, Toronto Western Hospital, Toronto, Ontario, Canada
| | - Madison Remick
- Department of Neurological Surgery, University of Pittsburgh, Pittsburgh, Pennsylvania
| | - George M Ibrahim
- Division of Neurosurgery, Department of Surgery, University of Toronto, Toronto, Ontario, Canada.,Division of Neurosurgery, Hospital for Sick Children, Program in Neuroscience and Mental Health, Hospital for Sick Children Research Institute, Toronto, Ontario, Canada
| | - Taylor J Abel
- Department of Neurological Surgery, University of Pittsburgh, Pittsburgh, Pennsylvania
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Frauscher B, Gotman J. Sleep, oscillations, interictal discharges, and seizures in human focal epilepsy. Neurobiol Dis 2019; 127:545-553. [DOI: 10.1016/j.nbd.2019.04.007] [Citation(s) in RCA: 40] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/05/2019] [Revised: 04/01/2019] [Accepted: 04/10/2019] [Indexed: 12/20/2022] Open
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Park CJ, Hong SB. High Frequency Oscillations in Epilepsy: Detection Methods and Considerations in Clinical Application. J Epilepsy Res 2019; 9:1-13. [PMID: 31482052 PMCID: PMC6706641 DOI: 10.14581/jer.19001] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/08/2017] [Revised: 01/02/2019] [Accepted: 01/04/2019] [Indexed: 01/10/2023] Open
Abstract
High frequency oscillations (HFOs) is a brain activity observed in electroencephalography (EEG) in frequency ranges between 80–500 Hz. HFOs can be classified into ripples (80–200 Hz) and fast ripples (200–500 Hz) by their distinctive characteristics. Recent studies reported that both ripples and fast fipples can be regarded as a new biomarker of epileptogenesis and ictogenesis. Previous studies verified that HFOs are clinically important both in patients with mesial temporal lobe epilepsy and neocortical epilepsy. Also, in epilepsy surgery, patients with higher resection ratio of brain regions with HFOs showed better outcome than a group with lower resection ratio. For clinical application of HFOs, it is important to delineate HFOs accurately and discriminate them from artifacts. There have been technical improvements in detecting HFOs by developing various detection algorithms. Still, there is a difficult issue on discriminating clinically important HFOs among detected HFOs, where both quantitative and subjective approaches are suggested. This paper is a review on published HFO studies focused on clinical findings and detection techniques of HFOs as well as tips for clinical applications.
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Affiliation(s)
- Chae Jung Park
- Department of Neurology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Korea.,Samsung Biomedical Research Institute (SBRI), Seoul, Korea
| | - Seung Bong Hong
- Department of Neurology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Korea.,Samsung Biomedical Research Institute (SBRI), Seoul, Korea
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Ewell LA, Fischer KB, Leibold C, Leutgeb S, Leutgeb JK. The impact of pathological high-frequency oscillations on hippocampal network activity in rats with chronic epilepsy. eLife 2019; 8:42148. [PMID: 30794155 PMCID: PMC6386518 DOI: 10.7554/elife.42148] [Citation(s) in RCA: 39] [Impact Index Per Article: 7.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/18/2018] [Accepted: 02/09/2019] [Indexed: 11/29/2022] Open
Abstract
In epilepsy, brain networks generate pathological high-frequency oscillations (pHFOs) during interictal periods. To understand how pHFOs differ from normal oscillations in overlapping frequency bands and potentially perturb hippocampal processing, we performed high-density single unit and local field potential recordings from hippocampi of behaving rats with and without chronic epilepsy. In epileptic animals, we observed two types of co-occurring fast oscillations, which by comparison to control animals we could classify as ‘ripple-like’ or ‘pHFO’. We compared their spectral characteristics, brain state dependence, and cellular participants. Strikingly, pHFO occurred irrespective of brain state, were associated with interictal spikes, engaged distinct subnetworks of principal neurons compared to ripple-like events, increased the sparsity of network activity, and initiated both general and immediate disruptions in spatial information coding. Taken together, our findings suggest that events that result in pHFOs have an immediate impact on memory processes, corroborating the need for proper classification of pHFOs to facilitate therapeutic interventions that selectively target pathological activity.
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Affiliation(s)
- Laura A Ewell
- Neurobiology Section and Center for Neural Circuits and Behavior, Division of Biological Sciences, University of California, San Diego, La Jolla, United States.,Institute of Experimental Epileptology and Cognition Research, University of Bonn Medical Center, Bonn, Germany
| | - Kyle B Fischer
- Neurobiology Section and Center for Neural Circuits and Behavior, Division of Biological Sciences, University of California, San Diego, La Jolla, United States.,Neuroscience Graduate Program, University of California, San Diego, La Jolla, United States
| | - Christian Leibold
- Department Biologie II, Ludwig-Maximilians-Universität München, Martinsried, Germany.,Berstein Center for Computational Neuroscience Munich, Martinried, Germany
| | - Stefan Leutgeb
- Neurobiology Section and Center for Neural Circuits and Behavior, Division of Biological Sciences, University of California, San Diego, La Jolla, United States.,Kavli Institute for Brain and Mind, University of California, San Diego, La Jolla, United States
| | - Jill K Leutgeb
- Neurobiology Section and Center for Neural Circuits and Behavior, Division of Biological Sciences, University of California, San Diego, La Jolla, United States
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Thomschewski A, Hincapié AS, Frauscher B. Localization of the Epileptogenic Zone Using High Frequency Oscillations. Front Neurol 2019; 10:94. [PMID: 30804887 PMCID: PMC6378911 DOI: 10.3389/fneur.2019.00094] [Citation(s) in RCA: 77] [Impact Index Per Article: 15.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/08/2018] [Accepted: 01/23/2019] [Indexed: 01/22/2023] Open
Abstract
For patients with drug-resistant focal epilepsy, surgery is the therapy of choice in order to achieve seizure freedom. Epilepsy surgery foremost requires the identification of the epileptogenic zone (EZ), defined as the brain area indispensable for seizure generation. The current gold standard for identification of the EZ is the seizure-onset zone (SOZ). The fact, however that surgical outcomes are unfavorable in 40-50% of well-selected patients, suggests that the SOZ is a suboptimal biomarker of the EZ, and that new biomarkers resulting in better postsurgical outcomes are needed. Research of recent years suggested that high-frequency oscillations (HFOs) are a promising biomarker of the EZ, with a potential to improve surgical success in patients with drug-resistant epilepsy without the need to record seizures. Nonetheless, in order to establish HFOs as a clinical biomarker, the following issues need to be addressed. First, evidence on HFOs as a clinically relevant biomarker stems predominantly from retrospective assessments with visual marking, leading to problems of reproducibility and reliability. Prospective assessments of the use of HFOs for surgery planning using automatic detection of HFOs are needed in order to determine their clinical value. Second, disentangling physiologic from pathologic HFOs is still an unsolved issue. Considering the appearance and the topographic location of presumed physiologic HFOs could be immanent for the interpretation of HFO findings in a clinical context. Third, recording HFOs non-invasively via scalp electroencephalography (EEG) and magnetoencephalography (MEG) is highly desirable, as it would provide us with the possibility to translate the use of HFOs to the scalp in a large number of patients. This article reviews the literature regarding these three issues. The first part of the article focuses on the clinical value of invasively recorded HFOs in localizing the EZ, the detection of HFOs, as well as their separation from physiologic HFOs. The second part of the article focuses on the current state of the literature regarding non-invasively recorded HFOs with emphasis on findings and technical considerations regarding their localization.
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Affiliation(s)
- Aljoscha Thomschewski
- Department of Neurology, Christian Doppler Medical Center, Paracelsus Medical University, Salzburg, Austria,Department of Psychology, Paris-Lodron University of Salzburg, Salzburg, Austria
| | - Ana-Sofía Hincapié
- Montreal Neurological Institute and Hospital, McGill University, Montreal, QC, Canada
| | - Birgit Frauscher
- Montreal Neurological Institute and Hospital, McGill University, Montreal, QC, Canada,*Correspondence: Birgit Frauscher
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Höller P, Trinka E, Höller Y. High-Frequency Oscillations in the Scalp Electroencephalogram: Mission Impossible without Computational Intelligence. Comput Intell Neurosci 2018; 2018:1638097. [PMID: 30158959 PMCID: PMC6109569 DOI: 10.1155/2018/1638097] [Citation(s) in RCA: 16] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 05/16/2018] [Revised: 06/20/2018] [Accepted: 07/12/2018] [Indexed: 01/22/2023]
Abstract
High-frequency oscillations (HFOs) in the electroencephalogram (EEG) are thought to be a promising marker for epileptogenicity. A number of automated detection algorithms have been developed for reliable analysis of invasively recorded HFOs. However, invasive recordings are not widely applicable since they bear risks and costs, and the harm of the surgical intervention of implantation needs to be weighted against the informational benefits of the invasive examination. In contrast, scalp EEG is widely available at low costs and does not bear any risks. However, the detection of HFOs on the scalp represents a challenge that was taken on so far mostly via visual detection. Visual detection of HFOs is, in turn, highly time-consuming and subjective. In this review, we discuss that automated detection algorithms for detection of HFOs on the scalp are highly warranted because the available algorithms were all developed for invasively recorded EEG and do not perform satisfactorily in scalp EEG because of the low signal-to-noise ratio and numerous artefacts as well as physiological activity that obscures the tiny phenomena in the high-frequency range.
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Affiliation(s)
- Peter Höller
- Department of Neurology, Christian Doppler Medical Centre and Centre for Cognitive Neuroscience, Spinal Cord Injury and Tissue Regeneration Center, Paracelsus Medical University, Salzburg, Austria
| | - Eugen Trinka
- Department of Neurology, Christian Doppler Medical Centre and Centre for Cognitive Neuroscience, Spinal Cord Injury and Tissue Regeneration Center, Paracelsus Medical University, Salzburg, Austria
| | - Yvonne Höller
- Department of Neurology, Christian Doppler Medical Centre and Centre for Cognitive Neuroscience, Spinal Cord Injury and Tissue Regeneration Center, Paracelsus Medical University, Salzburg, Austria
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Al-Bakri AF, Yaghouby F, Besio W, Ding L, Modur P, Sunderam S. Effect of Vigilance Changes on the Incidence of High Frequency Oscillations in the Epileptic Brain. Annu Int Conf IEEE Eng Med Biol Soc 2018; 2018:991-994. [PMID: 30440557 DOI: 10.1109/embc.2018.8512339] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/09/2023]
Abstract
Recent studies show that the rate of cortical high frequency oscillations (HFOs) differentiates epileptogenic tissue in individuals with epilepsy. However, HFO occurrence can vary widely with vigilance state. In this study we attempt to characterize this variation, which has implications for the choice of a suitable diagnostic baseline for spatiotemporal analysis of HFO activity. We analyzed simultaneous recordings of the scalp electroencephalogram (EEG) and the electrocorticogram (ECoG) to examine the correlation of HFO activity with vigilance state. We detected HFOs (80-500 Hz) from all bipolar ECoG derivations using the well-known Staba algorithm in ten seizure-free overnight recordings from five patients being evaluated for surgery. In addition, we classified EEG features using a linkage tree into four vigilance states representing gradations in sleep depth from wakefulness to slow wave sleep. Finally, we examined the correlation between vigilance state and HFO occurrence in the five channels with the most HFOs in each recording. The proportion of 30-s epochs containing HFOs was found to increase significantly with sleep depth (p<0.01). Further analysis is necessary to examine the effects of epoch length and sample size in the choice of diagnostic baseline.
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Spring AM, Pittman DJ, Aghakhani Y, Jirsch J, Pillay N, Bello-Espinosa LE, Josephson C, Federico P. Generalizability of High Frequency Oscillation Evaluations in the Ripple Band. Front Neurol 2018; 9:510. [PMID: 30002645 PMCID: PMC6031752 DOI: 10.3389/fneur.2018.00510] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/03/2017] [Accepted: 06/11/2018] [Indexed: 11/29/2022] Open
Abstract
Objective: We examined the interrater reliability and generalizability of high-frequency oscillation (HFO) visual evaluations in the ripple (80–250 Hz) band, and established a framework for the transition of HFO analysis to routine clinical care. We were interested in the interrater reliability or epoch generalizability to describe how similar the evaluations were between reviewers, and in the reviewer generalizability to represent the consistency of the internal threshold each individual reviewer. Methods: We studied 41 adult epilepsy patients (mean age: 35.6 years) who underwent intracranial electroencephalography. A morphology detector was designed and used to detect candidate HFO events, lower-threshold events, and distractor events. These events were subsequently presented to six expert reviewers, who visually evaluated events for the presence of HFOs. Generalizability theory was used to characterize the epoch generalizability (interrater reliability) and reviewer generalizability (internal threshold consistency) of visual evaluations, as well as to project the numbers of epochs, reviewers, and datasets required to achieve strong generalizability (threshold of 0.8). Results: The reviewer generalizability was almost perfect (0.983), indicating there were sufficient evaluations to determine the internal threshold of each reviewer. However, the interrater reliability for 6 reviewers (0.588) and pairwise interrater reliability (0.322) were both poor, indicating that the agreement of 6 reviewers is insufficient to reliably establish the presence or absence of individual HFOs. Strong interrater reliability (≥0.8) was projected as requiring a minimum of 17 reviewers, while strong reviewer generalizability could be achieved with <30 epoch evaluations per reviewer. Significance: This study reaffirms the poor reliability of using small numbers of reviewers to identify HFOs, and projects the number of reviewers required to overcome this limitation. It also provides a set of tools which may be used for training reviewers, tracking changes to interrater reliability, and for constructing a benchmark set of epochs that can serve as a generalizable gold standard, against which other HFO detection algorithms may be compared. This study represents an important step toward the reconciliation of important but discordant findings from HFO studies undertaken with different sets of HFOs, and ultimately toward transitioning HFO analysis into a meaningful part of the clinical epilepsy workup.
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Affiliation(s)
- Aaron M Spring
- Department of Clinical Neurosciences, University of Calgary, Calgary, AB, Canada.,Hotchkiss Brain Institute, University of Calgary, Calgary, AB, Canada.,Seaman Family MR Research Centre, Foothills Medical Centre, Calgary, AB, Canada
| | - Daniel J Pittman
- Hotchkiss Brain Institute, University of Calgary, Calgary, AB, Canada.,Seaman Family MR Research Centre, Foothills Medical Centre, Calgary, AB, Canada
| | - Yahya Aghakhani
- Department of Clinical Neurosciences, University of Calgary, Calgary, AB, Canada
| | - Jeffrey Jirsch
- Department of Medicine, University of Alberta, Edmonton, AB, Canada
| | - Neelan Pillay
- Department of Clinical Neurosciences, University of Calgary, Calgary, AB, Canada
| | - Luis E Bello-Espinosa
- Department of Clinical Neurosciences, University of Calgary, Calgary, AB, Canada.,Department of Paediatrics, University of Calgary, Calgary, AB, Canada
| | - Colin Josephson
- Department of Clinical Neurosciences, University of Calgary, Calgary, AB, Canada
| | - Paolo Federico
- Department of Clinical Neurosciences, University of Calgary, Calgary, AB, Canada.,Hotchkiss Brain Institute, University of Calgary, Calgary, AB, Canada.,Seaman Family MR Research Centre, Foothills Medical Centre, Calgary, AB, Canada.,Department of Radiology, University of Calgary, Calgary, AB, Canada
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Khadjevand F, Cimbalnik J, Worrell GA. Progress and Remaining Challenges in the Application of High Frequency Oscillations as Biomarkers of Epileptic Brain. Curr Opin Biomed Eng 2017. [PMID: 29532041 DOI: 10.1016/j.cobme.2017.09.006] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/16/2023]
Abstract
High-frequency oscillations (HFOs: 100 - 600 Hz) have been widely proposed as biomarkers of epileptic brain tissue. In addition, HFOs over a broader range of frequencies spanning 30 - 2000 Hz are potential biomarkers of both physiological and pathological brain processes. The majority of the results from humans with focal epilepsy have focused on HFOs recorded directly from the brain with intracranial EEG (iEEG) in the high gamma (65 - 100 Hz), ripple (100 - 250 Hz), and fast ripple (250 - 600 Hz) frequency ranges. These results are supplemented by reports of HFOs recorded with iEEG in the low gamma (30 - 65Hz) and very high frequency (500 - 2000 Hz) ranges. Visual detection of HFOs is laborious and limited by poor inter-rater agreement; and the need for accurate, reproducible automated HFOs detection is well recognized. In particular, the clinical translation of HFOs as a biomarker of the epileptogenic brain has been limited by the ability to reliably detect and accurately classify HFOs as physiological or pathological. Despite these challenges, there has been significant progress in the field, which is the subject of this review. Furthermore, we provide data and corresponding analytic code in an effort to promote reproducible research and accelerate clinical translation.
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Affiliation(s)
- Fatemeh Khadjevand
- Mayo Systems Electrophysiology Laboratory, Department of Neurology, Mayo Clinic, 200 First St SW, Rochester MN, 55905, USA
| | - Jan Cimbalnik
- Mayo Systems Electrophysiology Laboratory, Department of Neurology, Mayo Clinic, 200 First St SW, Rochester MN, 55905, USA.,International Clinical Research Center, St. Anne's University Hospital, Brno, Czech Republic
| | - Gregory A Worrell
- Mayo Systems Electrophysiology Laboratory, Department of Neurology, Mayo Clinic, 200 First St SW, Rochester MN, 55905, USA.,Department of Biomedical Engineering and Physiology, Mayo Clinic, 200 First St SW, Rochester MN, 55905, USA
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Frauscher B, Bartolomei F, Kobayashi K, Cimbalnik J, van 't Klooster MA, Rampp S, Otsubo H, Höller Y, Wu JY, Asano E, Engel J, Kahane P, Jacobs J, Gotman J. High-frequency oscillations: The state of clinical research. Epilepsia 2017; 58:1316-1329. [PMID: 28666056 DOI: 10.1111/epi.13829] [Citation(s) in RCA: 209] [Impact Index Per Article: 29.9] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 05/25/2017] [Indexed: 01/03/2023]
Abstract
Modern electroencephalographic (EEG) technology contributed to the appreciation that the EEG signal outside the classical Berger frequency band contains important information. In epilepsy, research of the past decade focused particularly on interictal high-frequency oscillations (HFOs) > 80 Hz. The first large application of HFOs was in the context of epilepsy surgery. This is now followed by other applications such as assessment of epilepsy severity and monitoring of antiepileptic therapy. This article reviews the evidence on the clinical use of HFOs in epilepsy with an emphasis on the latest developments. It highlights the growing literature on the association between HFOs and postsurgical seizure outcome. A recent meta-analysis confirmed a higher resection ratio for HFOs in seizure-free versus non-seizure-free patients. Residual HFOs in the postoperative electrocorticogram were shown to predict epilepsy surgery outcome better than preoperative HFO rates. The review further discusses the different attempts to separate physiological from epileptic HFOs, as this might increase the specificity of HFOs. As an example, analysis of sleep microstructure demonstrated a different coupling between HFOs inside and outside the epileptogenic zone. Moreover, there is increasing evidence that HFOs are useful to measure disease activity and assess treatment response using noninvasive EEG and magnetoencephalography. This approach is particularly promising in children, because they show high scalp HFO rates. HFO rates in West syndrome decrease after adrenocorticotropic hormone treatment. Presence of HFOs at the time of rolandic spikes correlates with seizure frequency. The time-consuming visual assessment of HFOs, which prevented their clinical application in the past, is now overcome by validated computer-assisted algorithms. HFO research has considerably advanced over the past decade, and use of noninvasive methods will make HFOs accessible to large numbers of patients. Prospective multicenter trials are awaited to gather information over long recording periods in large patient samples.
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Affiliation(s)
- Birgit Frauscher
- Department of Medicine and Center for Neuroscience Studies, Queen's University, Kingston, Ontario, Canada
| | - Fabrice Bartolomei
- National Institute of Health and Medical Research, Institute of Neurosciences of Systems, Aix Marseille University, Marseille, France
| | - Katsuhiro Kobayashi
- Department of Child Neurology, Okayama University Graduate School of Medicine, Dentistry and Pharmaceutical Sciences, Okayama University Hospital, Kita-ku, Okayama, Japan
| | - Jan Cimbalnik
- International Clinical Research Center, St. Anne's University Hospital, Brno, Czech Republic
| | - Maryse A van 't Klooster
- Department of Neurology and Neurosurgery, Brain Center Rudolf Magnus, University Medical Center Utrecht, Utrecht, The Netherlands
| | - Stefan Rampp
- Department of Neurosurgery, University Hospital Erlangen, Erlangen, Germany
| | - Hiroshi Otsubo
- Division of Neurology, Department of Pediatrics, Hospital for Sick Children, Toronto, Ontario, Canada
| | - Yvonne Höller
- Department of Neurology, Christian Doppler Medical Center and Center for Cognitive Neuroscience, Paracelsus Medical University Salzburg, Salzburg, Austria
| | - Joyce Y Wu
- Division of Pediatric Neurology, Mattel Children's Hospital at UCLA, Los Angeles, California, U.S.A
| | - Eishi Asano
- Departments of Pediatrics and Neurology, Detroit Medical Center, Children's Hospital of Michigan, Wayne State University, Detroit, Michigan, U.S.A
| | - Jerome Engel
- Departments of Neurology, Neurobiology, and Psychiatry, Brain Research Institute, University of California, Los Angeles, Los Angeles, California, U.S.A
| | - Philippe Kahane
- Department of Neurology, Grenoble-Alpes University Hospital and Grenoble-Alpes University, Grenoble, France
| | - Julia Jacobs
- Department of Neuropediatrics and Muscular Diseases, University Medical Center Freiburg, Freiburg, Germany
| | - Jean Gotman
- Montreal Neurological Institute and Hospital, McGill University, Montreal, Quebec, Canada
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Jeong JW, Asano E, Kumar Pilli V, Nakai Y, Chugani HT, Juhász C. Objective 3D surface evaluation of intracranial electrophysiologic correlates of cerebral glucose metabolic abnormalities in children with focal epilepsy. Hum Brain Mapp 2017; 38:3098-3112. [PMID: 28322026 DOI: 10.1002/hbm.23577] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/15/2016] [Revised: 03/01/2017] [Accepted: 03/09/2017] [Indexed: 12/27/2022] Open
Abstract
To determine the spatial relationship between 2-deoxy-2[18 F]fluoro-D-glucose (FDG) metabolic and intracranial electrophysiological abnormalities in children undergoing two-stage epilepsy surgery, statistical parametric mapping (SPM) was used to correlate hypo- and hypermetabolic cortical regions with ictal and interictal electrocorticography (ECoG) changes mapped onto the brain surface. Preoperative FDG-PET scans of 37 children with intractable epilepsy (31 with non-localizing MRI) were compared with age-matched pseudo-normal pediatric control PET data. Hypo-/hypermetabolic maps were transformed to 3D-MRI brain surface to compare the locations of metabolic changes with electrode coordinates of the ECoG-defined seizure onset zone (SOZ) and interictal spiking. While hypometabolic clusters showed a good agreement with the SOZ on the lobar level (sensitivity/specificity = 0.74/0.64), detailed surface-distance analysis demonstrated that large portions of ECoG-defined SOZ and interictal spiking area were located at least 3 cm beyond hypometabolic regions with the same statistical threshold (sensitivity/specificity = 0.18-0.25/0.94-0.90 for overlap 3-cm distance); for a lower threshold, sensitivity for SOZ at 3 cm increased to 0.39 with a modest compromise of specificity. Performance of FDG-PET SPM was slightly better in children with smaller as compared with widespread SOZ. The results demonstrate that SPM utilizing age-matched pseudocontrols can reliably detect the lobe of seizure onset. However, the spatial mismatch between metabolic and EEG epileptiform abnormalities indicates that a more complete SOZ detection could be achieved by extending intracranial electrode coverage at least 3 cm beyond the metabolic abnormality. Considering that the extent of feasible electrode coverage is limited, localization information from other modalities is particularly important to optimize grid coverage in cases of large hypometabolic cortex. Hum Brain Mapp 38:3098-3112, 2017. © 2017 Wiley Periodicals, Inc.
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Affiliation(s)
- Jeong-Won Jeong
- Departments of Pediatrics and Neurology, School of Medicine, Wayne State University, Detroit, Michigan.,Translational Imaging Laboratory, PET Center, Children's Hospital of Michigan, Detroit, Michigan
| | - Eishi Asano
- Departments of Pediatrics and Neurology, School of Medicine, Wayne State University, Detroit, Michigan
| | - Vinod Kumar Pilli
- Departments of Pediatrics and Neurology, School of Medicine, Wayne State University, Detroit, Michigan.,Translational Imaging Laboratory, PET Center, Children's Hospital of Michigan, Detroit, Michigan
| | - Yasuo Nakai
- Departments of Pediatrics and Neurology, School of Medicine, Wayne State University, Detroit, Michigan
| | - Harry T Chugani
- Department of Neurology, Nemours DuPont Hospital for Children, Wilmington, Delaware.,Thomas Jefferson University School of Medicine, Philadelphia, Pennysylvania
| | - Csaba Juhász
- Departments of Pediatrics and Neurology, School of Medicine, Wayne State University, Detroit, Michigan.,Translational Imaging Laboratory, PET Center, Children's Hospital of Michigan, Detroit, Michigan
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Spring AM, Pittman DJ, Aghakhani Y, Jirsch J, Pillay N, Bello-espinosa LE, Josephson C, Federico P. Interrater reliability of visually evaluated high frequency oscillations. Clin Neurophysiol 2017; 128:433-41. [DOI: 10.1016/j.clinph.2016.12.017] [Citation(s) in RCA: 45] [Impact Index Per Article: 6.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/10/2016] [Revised: 11/13/2016] [Accepted: 12/15/2016] [Indexed: 02/01/2023]
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von Ellenrieder N, Dubeau F, Gotman J, Frauscher B. Physiological and pathological high-frequency oscillations have distinct sleep-homeostatic properties. Neuroimage Clin 2017; 14:566-573. [PMID: 28337411 PMCID: PMC5349616 DOI: 10.1016/j.nicl.2017.02.018] [Citation(s) in RCA: 45] [Impact Index Per Article: 6.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/09/2016] [Revised: 02/08/2017] [Accepted: 02/22/2017] [Indexed: 01/23/2023]
Abstract
OBJECTIVE The stage of sleep is a known modulator of high-frequency oscillations (HFOs). For instance, high amplitude slow waves during NREM sleep and the subtypes of REM sleep were shown to contribute to a better separation between physiological and pathological HFOs. This study investigated rates and spatial spread of the different HFO types (physiological and pathological ripples in the 80-250 Hz frequency band, and fast ripples above 250 Hz) depending on time spent in sleep across the different sleep cycles. METHODS Fifteen patients with focal pharmaco-resistant epilepsy underwent one night of video-polysomnography during chronic intracranial EEG recording for presurgical epilepsy evaluation. The HFO rate and spread across the different sleep cycles were determined with an automatic HFO detector. We built models to explain the observed rate and spread based on time in sleep and other variables i.e. sleep stage, delta band and sigma band activity, and slow wave amplitude. Statistical significance of the different variables was determined by a model comparison using the Akaike information criterion. RESULTS The rate of HFOs depends significantly on the accumulated time of sleep. As the night advanced, the rate of pathological ripples and fast ripples decreased during NREM sleep (up to 15% per hour spent in the respective sleep stages), while the rate of physiological ripples increased during REM sleep (8% per hour spent in REM sleep). Interestingly, the stage of sleep but not the sleep cycle determined the extent of spread of HFOs, showing a larger field during NREM sleep and a more restricted field during REM sleep. CONCLUSION The different dependence with sleep time for physiological and pathological ripples is in keeping with their distinct underlying generating mechanisms. From a practical point of view, the first sleep cycle seems to be best suitable for studying HFOs in epilepsy, given that the contrast between physiological and pathological ripple rates is largest during this time.
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Affiliation(s)
- Nicolás von Ellenrieder
- Montreal Neurological Institute and Hospital, McGill University, 3801 University Street, Montreal H3A 2B4, Québec, Canada
| | - François Dubeau
- Montreal Neurological Institute and Hospital, McGill University, 3801 University Street, Montreal H3A 2B4, Québec, Canada
| | - Jean Gotman
- Montreal Neurological Institute and Hospital, McGill University, 3801 University Street, Montreal H3A 2B4, Québec, Canada
| | - Birgit Frauscher
- Montreal Neurological Institute and Hospital, McGill University, 3801 University Street, Montreal H3A 2B4, Québec, Canada
- Department of Medicine and Center for Neuroscience Studies, Queen's University, 18 Stuart Street, Kingston K7L3N6, Ontario, Canada
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Nonoda Y, Miyakoshi M, Ojeda A, Makeig S, Juhász C, Sood S, Asano E. Interictal high-frequency oscillations generated by seizure onset and eloquent areas may be differentially coupled with different slow waves. Clin Neurophysiol 2016; 127:2489-99. [PMID: 27178869 DOI: 10.1016/j.clinph.2016.03.022] [Citation(s) in RCA: 74] [Impact Index Per Article: 9.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/15/2015] [Revised: 03/17/2016] [Accepted: 03/22/2016] [Indexed: 11/19/2022]
Abstract
OBJECTIVE High-frequency oscillations (HFOs) can be spontaneously generated by seizure-onset and functionally-important areas. We determined if consideration of the spectral frequency bands of coupled slow-waves could distinguish between epileptogenic and physiological HFOs. METHODS We studied a consecutive series of 13 children with focal epilepsy who underwent extraoperative electrocorticography. We measured the occurrence rate of HFOs during slow-wave sleep at each electrode site. We subsequently determined the performance of HFO rate for localization of seizure-onset sites and undesirable detection of nonepileptic sensorimotor-visual sites defined by neurostimulation. We likewise determined the predictive performance of modulation index: MI(XHz)&(YHz), reflecting the strength of coupling between amplitude of HFOsXHz and phase of slow-waveYHz. The predictive accuracy was quantified using the area under the curve (AUC) on receiver-operating characteristics analysis. RESULTS Increase in HFO rate localized seizure-onset sites (AUC⩾0.72; p<0.001), but also undesirably detected nonepileptic sensorimotor-visual sites (AUC⩾0.58; p<0.001). Increase in MI(HFOs)&(3-4Hz) also detected both seizure-onset (AUC⩾0.74; p<0.001) and nonepileptic sensorimotor-visual sites (AUC⩾0.59; p<0.001). Increase in subtraction-MIHFOs [defined as subtraction of MI(HFOs)&(0.5-1Hz) from MI(HFOs)&(3-4Hz)] localized seizure-onset sites (AUC⩾0.71; p<0.001), but rather avoided detection of nonepileptic sensorimotor-visual sites (AUC⩽0.42; p<0.001). CONCLUSION Our data suggest that epileptogenic HFOs may be coupled with slow-wave3-4Hz more preferentially than slow-wave0.5-1Hz, whereas physiologic HFOs with slow-wave0.5-1Hz more preferentially than slow-wave3-4Hz during slow-wave sleep. SIGNIFICANCE Further studies in larger samples are warranted to determine if consideration of the spectral frequency bands of slow-waves coupled with HFOs can positively contribute to presurgical evaluation of patients with focal epilepsy.
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Affiliation(s)
- Yutaka Nonoda
- Pediatrics, Wayne State University, Children's Hospital of Michigan, Detroit, MI, USA
| | - Makoto Miyakoshi
- Swartz Center for Computational Neuroscience, Institute for Neural Computation, University of California San Diego, La Jolla, CA, USA
| | - Alejandro Ojeda
- Swartz Center for Computational Neuroscience, Institute for Neural Computation, University of California San Diego, La Jolla, CA, USA
| | - Scott Makeig
- Swartz Center for Computational Neuroscience, Institute for Neural Computation, University of California San Diego, La Jolla, CA, USA
| | - Csaba Juhász
- Pediatrics, Wayne State University, Children's Hospital of Michigan, Detroit, MI, USA; Neurology, Wayne State University, Children's Hospital of Michigan, Detroit, MI, USA
| | - Sandeep Sood
- Neurosurgery, Wayne State University, Children's Hospital of Michigan, Detroit, MI, USA
| | - Eishi Asano
- Pediatrics, Wayne State University, Children's Hospital of Michigan, Detroit, MI, USA; Neurology, Wayne State University, Children's Hospital of Michigan, Detroit, MI, USA.
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